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        <title>Frontiers in Imaging | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/imaging</link>
        <description>RSS Feed for Frontiers in Imaging | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-04-23T05:17:20.884+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2026.1758694</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2026.1758694</link>
        <title><![CDATA[Feasibility in the detection of sentinel lymph node-associated blood vessels using intravital microscopy in patients undergoing sentinel lymph node biopsy for melanoma]]></title>
        <pubdate>2026-03-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Emmanuel Gabriel</author><author>Daniel T. Fisher</author><author>Minhyung Kim</author><author>Kristopher Attwood</author><author>Xiaoyi Ma</author><author>Valerie Francescutti</author><author>John M. Kane</author><author>Sharon S. Evans</author><author>Joseph J. Skitzki</author>
        <description><![CDATA[While the clinical focus on the sentinel lymph node biopsy (SLNB) is the presence of intra- or extra-nodal metastases, preclinical studies suggest that tumor-draining SLNB-associated vascular architecture and adhesion properties are altered regardless of SLNB positivity. Human intravital microscopy (HIVM) has defined blood vessel abnormalities that may impact lymphocyte adhesion and systemic drug delivery at primary melanoma sites. In this pilot study of HIVM during melanoma SLNB, we sought to determine the feasibility of obtaining HIVM observations of SLNB-associated vessels. We successfully performed HIVM in all 20 SLNB patients, and 7 were found to have nodal micrometastases by standard pathology. HIVM was capable of identifying both functional and non-functional SLNB-associated vessels based on the presence or absence of fluorescent dye uptake, respectively. Comparing vessel characteristics as a secondary exploratory objective, no statistically significant differences were noted in the diameter, flow rate, functionality, or shear stress of SLNB-associated blood vessels between positive and negative SLNBs, which may likely have been a reflection of the minimal disease burden. Nonetheless, these initial observations provide the framework to optimize future trials of HIVM in cancer patients.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2026.1752625</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2026.1752625</link>
        <title><![CDATA[Enhancement of multi-objective Darwinian particle swarm optimization for neural-network-based multimodal medical image fusion]]></title>
        <pubdate>2026-02-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chisom E. Ogbuanya</author>
        <description><![CDATA[The purpose of this research is to develop a multimodal medical image fusion method that will provide high-performance fusion images at a speed high enough for efficient real-time image-guided surgeries. This paper therefore proposes an improved multi-objective Darwinian particle swarm optimization method that incorporates a fractional calculus operator for effective multimodal medical image fusion. This is because multimodal medical image fusion is essential in many clinical diagnoses, and it represents a multi-objective problem due to the important objective indicators for measuring its efficiencies, such as the parameters of the neural network and the speed of the fusion process. The proposed method aims to optimize the Tsallis cross-entropy as a stimulating input to the pulse-coupled neural network (PCNN) for multimodal image fusion. In this work, multi-objective Darwinian particle swarm optimization (MODPSO) is utilized due to its ability to escape local optima more effectively than classical multi-objective particle swarm optimization (MOPSO). The approach uses the fact that the convergence rate of MODPSO is improved by introducing a fractional calculus operator, which is incorporated into the updating formulas for the velocity and position of the particles. The PCNN output serves as an optimal parameter for fusing the high-frequency coefficients of decomposed source images, which are initially decomposed into low- and high-frequency subbands. The low-frequency coefficients are fused using an averaging method. Results obtained in this paper show that the proposed method yields the highest average accuracy of 90.7% after a three-fold cross-validation was carried out with a small dataset extracted from a larger available dataset. In conclusion, the experimental results demonstrate the superiority of the proposed method over comparative methods in terms of both visual quality and quantitative evaluation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2026.1725794</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2026.1725794</link>
        <title><![CDATA[Aluminum impairs cellular ultrastructure and bone microarchitecture in newborn rats]]></title>
        <pubdate>2026-02-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mara Rubia Marques</author><author>Anderson Camargo Moreira</author><author>Iara Frangiotti Mantovani</author><author>Pedro Vale de Azevedo Brito</author><author>Isabela Cristina Gomes de Souza Nascimento</author><author>Celso Peres Fernandes</author><author>Fernanda Cristina Alcantara dos Santos</author>
        <description><![CDATA[Modern lifestyle is strongly marked by the presence of aluminum (Al) in practically all human consumer products. Bone tissue is one of the main sites of Al accumulation, and its toxic effects are well known in individuals subjected to chronic exposure. However, there is still a gap in knowledge regarding the effects of Al on bone formation in the neonatal period. This study evaluated the effect of Al ingestion on rat tibiae during the neonatal period. Wistar rats were divided into control and Al groups. The Al group received AlCl3 (2.02 mg/kg/day) via gavage for fifteen days, then, the right tibiae were used to evaluate osteoblast and osteocyte ultrastructure and bone microarchitecture using transmission electron microscopy and computed X-ray microtomography, respectively. Al promoted swelling and altered mitochondrial crests in osteoblasts. Osteocytes showed accumulation of electron-dense lysosomes and absence of the osmiophilic lamina in the lacunae, showing characteristics similar to osteocytic osteolysis. Cortical Thickness (Ct.Th), Trabecular thickness (Tb.th) and trabecular number (Tb.N) decreased whilst trabecular spacing (Tb.Sp) increased. These results suggest that Al intake during the neonatal period may affect the function of osteoblasts and osteocytes besides compromising bone formation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1694840</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1694840</link>
        <title><![CDATA[Cardiac adipose tissue, imaging segmentation, and quantification for cardiovascular disease assessment]]></title>
        <pubdate>2026-01-08T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Julian Rene Cuellar Buritica</author><author>Mukul Bhattarai</author><author>Pedro Carrillo</author><author>Manjula Burri</author><author>Jon Klingensmith</author>
        <description><![CDATA[Cardiac adipose tissue (CAT) has emerged as a critical and clinically relevant factor in cardiovascular disease (CVD), yet its full impact remains largely overlooked. The amount of fat surrounding the heart can influence major blood vessels by promoting plaque formation. In conditions such as cardiac steatosis or fatty heart disease, fat infiltration or accumulation within the heart muscle compromises its function may play a role in heart failure (HF) and coronary artery disease (CAD). This review explores the different types of fat deposits surrounding the heart, focusing on the potential contribution of CAT to cardiovascular disease (CVD). Three main imaging modalities for assessing cardiac fat are discussed, including magnetic resonance imaging (MRI), computed tomography (CT), and echocardiography. The segmentation and quantification of the fat for each imaging modality are also presented, correlating these measurements with CVD risk. Each imaging modality offers distinct advantages and limitations in segmenting and quantifying fat. Despite its clinical significance, quantification and characterization of CAT remain challenging, requiring advanced imaging techniques for precise assessment. Future research should focus on unlocking the mechanistic pathways that link CAT to adverse cardiovascular outcomes, ultimately enhancing our ability to predict, prevent, and treat heart disease with greater precision. As imaging technology advances, there is a need for refined segmentation methods and consensus-driven guidelines to establish CAT as a key biomarker in CVD risk stratification.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1761718</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1761718</link>
        <title><![CDATA[Editorial: Deep learning for medical imaging applications]]></title>
        <pubdate>2026-01-06T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Simone Bonechi</author><author>Monica Bianchini</author><author>Paolo Andreini</author><author>Sandeep Kumar Mishra</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1610258</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1610258</link>
        <title><![CDATA[Advances in magnetic particle imaging: evaluating magnetic microspheres and optimized acquisition parameters for high sensitivity cell tracking]]></title>
        <pubdate>2025-07-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Samantha N. Flood</author><author>Paula J. Foster</author>
        <description><![CDATA[IntroductionThe sensitivity and resolution of magnetic particle imaging (MPI) depend on the choice of tracer and specific imaging parameters. For cell tracking applications with MPI, both the superparamagnetic iron oxide (SPIO) tracer and the cell labeling efficiency have a significant impact on MPI sensitivity and vary for different tracers.MethodsThis study compared three commercially available SPIO tracers (VivoTrax, Synomag-D and ProMag) and SPIO-labeled cells using magnetic particle relaxometry (MPR) and imaging. Further, the effect of imaging parameters (high and low gradient field strength and drive field amplitude) on MPI signal strength, resolution, and cell detection limits, was evaluated.ResultsThe peak MPI signal measured by MPR was much higher for Synomag-D compared to VivoTrax and ProMag. However, the signal for intracellular Synomag-D was significantly reduced. In contrast, the signal for ProMag, a micron-sized iron oxide (MPIO) particle, was not significantly different for free and intracellular particles. The cellular iron loading was higher for ProMag compared to Synomag-D. The total MPI signal measured from images of free and intracellular SPIOs was highest for ProMag. Varying imaging parameters confirmed that a lower gradient field strength and higher drive field amplitude improved tracer and cellular sensitivity.DiscussionThese results, in addition to prior work from our lab, suggest that MPIOs are a good option for cell tracking with MPI. In conclusion, the evaluation of tracers by MPR is not sufficient to predict the performance of all SPIO tracers; in particular, not for larger, polymer-encapsulated iron particles such as ProMag, or for SPIO tracers internalized in cells. Improvements in MPI sensitivity through lower gradient field strength and higher drive field amplitudes are associated with a trade-off in image resolution.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1476377</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1476377</link>
        <title><![CDATA[Template recovery attack on encrypted face recognition systems with unprotected decision using synthetic faces]]></title>
        <pubdate>2025-05-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Amina Bassit</author><author>Florian Hahn</author><author>Zohra Rezgui</author><author>Hatef Otroshi Shahreza</author><author>Raymond Veldhuis</author><author>Andreas Peter</author>
        <description><![CDATA[IntroductionHomomorphic encryption (HE) enables privacy-preserving face recognition by allowing encrypted facial embeddings to be compared without decryption. While efficient, these systems often reveal comparison scores in plaintext, introducing a security risk. Revealing these scores can potentially allow adversaries to reconstruct sensitive facial embeddings and infer demographic attributes, thus compromising user privacy.MethodsThis work proposes a training-less face template recovery attack leveraging the Lagrange multiplier optimization method. The attack requires only a small set of randomly generated synthetic facial images and their associated comparison scores with a target template. The method assumes attackers use spoofed synthetic faces and lack direct access to the face recognition system, aligning with real-world threat models.ResultsExperimental evaluation demonstrates the feasibility and effectiveness of the proposed attack. It shows that between 50 and 192 comparison scores and synthetic images are sufficient to recover the target face template with 100% success under strict system thresholds. The recovered templates closely resemble the original and retain identifiable soft biometric traits.DiscussionThe findings reveal a critical vulnerability in face recognition systems employing inner product similarity measures under homomorphic encryption. Even without system access or training data, attackers can exploit leaked comparison scores to compromise facial privacy. The study underscores the need to reassess how score leakage is handled in encrypted recognition systems and explore stronger protection mechanisms against template reconstruction.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1504551</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1504551</link>
        <title><![CDATA[High-quality deepfakes have a heart!]]></title>
        <pubdate>2025-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Clemens Seibold</author><author>Eric L. Wisotzky</author><author>Arian Beckmann</author><author>Benjamin Kossack</author><author>Anna Hilsmann</author><author>Peter Eisert</author>
        <description><![CDATA[IntroductionDeepfakes have become ubiquitous in our modern society, with both their quantity and quality increasing. The current evolution of image generation techniques makes the detection of manipulated content through visual inspection increasingly difficult. This challenge has motivated researchers to analyze heart-beat-related signal to distinguish deep fakes from genuine videos.MethodsIn this study, we analyze deepfake videos of faces generated with novel methods regarding their heart-beat-related signals using remote photoplethysmography (rPPG). The rPPG signal describes the blood flow based, or rather local blood volume changes, and thus reflects the pulse signal. For our analysis, we present a pipeline that extracts rPPG signals and investigate the origin of the extracted signals in deepfake videos using correlation analyses. To validate our rPPG extraction pipeline and analyze rPPG signals of deepfakes, we captured a dataset of facial videos synchronized with an electrocardiogram (ECG) as a ground-truth pulse signal. Additionally, we generated high-quality deepfakes and incorporated publicly available datasets into our evaluation.ResultsWe prove that our heart rate extraction pipeline produces valid estimates for genuine videos by comparing the estimated results with ECG reference data. Our high-quality deepfakes exhibit valid heart rates and their rPPG signals show a significant correlation with the corresponding driver video that was used to generate them. Furthermore, we show that this also holds for deepfakes from a publicly available dataset.DiscussionPrevious research assumed that the subtle heart-beat-related signals get lost during the deepfake generation process, making them useful for deepfake detection. However, this paper shows that this assumption is no longer valid for current deepfake methods. Nevertheless, preliminary experiments indicate that analyzing spatial distribution of bloodflow regarding its plausibility can still help to detect high quality deepfakes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1538533</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1538533</link>
        <title><![CDATA[Novel imaging approach for simultaneous tracking of cell dynamics in distinct tissue layers reveals cells involved in colonic peristalsis]]></title>
        <pubdate>2025-04-03T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Salah A. Baker</author><author>Peter J. Blair</author><author>Sharif Amit Kamran</author><author>Kenton M. Sanders</author>
        <description><![CDATA[We have developed a novel approach for high-resolution confocal imaging across multiple tissue planes simultaneously. By combining confocal microscopy, piezo actuators, and optogenetic sensors, we can simultaneously capture images of dynamic fluorescence signals from various cell populations in different tissue layers (Z planes). This enables the decoding of cell-to-cell communication through complex tissues, offering a significant advancement in understanding how cells in distinct layers of tissue communicate and coordinate their functions and produce integrated behaviors. For example, our technique sheds light on myogenic coordination underlying colonic motility. Examining various cell types, such as interstitial cells of Cajal (ICC) and smooth muscle cells (SMC), distributed through the thickness of muscle layers, we demonstrate distinct Ca2+ signaling patterns and organization that underlie complex colonic motor activities.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1547166</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1547166</link>
        <title><![CDATA[Continuous patient monitoring with AI: real-time analysis of video in hospital care settings]]></title>
        <pubdate>2025-03-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Paolo Gabriel</author><author>Peter Rehani</author><author>Tyler Troy</author><author>Tiffany Wyatt</author><author>Michael Choma</author><author>Narinder Singh</author>
        <description><![CDATA[IntroductionThis study introduces an AI-driven platform for continuous and passive patient monitoring in hospital settings, developed by LookDeep Health. Leveraging advanced computer vision, the platform provides real-time insights into patient behavior and interactions through video analysis, securely storing inference results in the cloud for retrospective evaluation.MethodsThe AI system detects key components in hospital rooms, including individuals' presence and roles, furniture location, motion magnitude, and boundary crossings. Inference results are securely stored in the cloud for retrospective evaluation. The dataset, compiled with 11 hospital partners, includes over 300 high-risk fall patients and spans more than 1,000 days of inference. An anonymized subset is publicly available to foster innovation and reproducibility at lookdeep/ai-norms-2024.ResultsPerformance evaluation demonstrates strong accuracy in object detection (macro F1-score = 0.92) and patient-role classification (F1-score = 0.98). The system reliably tracks the “patient alone” metric (mean logistic regression accuracy = 0.82 ± 0.15), enabling detection of patient isolation, wandering, and unsupervised movement-key indicators for fall risk and adverse events.DiscussionThis work establishes benchmarks for AI-driven patient monitoring, highlighting the platform's potential to enhance patient safety through continuous, data-driven insights into patient behavior and interactions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1436275</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1436275</link>
        <title><![CDATA[Exploring the correlation of radiomic features of ultrasound images and FNCLCC Grading of soft tissue sarcoma]]></title>
        <pubdate>2025-03-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chenyang Zhao</author><author>Yusen Zhang</author><author>Heng Lv</author><author>Nan Zhuang</author><author>Guangyin Yu</author><author>Yuzhou Shen</author><author>Licong Dong</author><author>Wangjie Wu</author><author>Lu Xie</author><author>Yun Tian</author><author>Zhaoling Yi</author><author>Desheng Sun</author><author>Xingen Wang</author><author>Haiqin Xie</author>
        <description><![CDATA[BackgroundPresurgical evaluation of the histopathological grade of soft tissue sarcoma (STS) is important for enacting treatment strategies. In this study, we plan to investigate the correlation of high-output ultrasound (US) radiomic features and the histopathological grade of STS.MethodsPatients with STS were retrospectively enrolled. The radiomic features were extracted from the US images of the STS lesions. The lesions were graded according to the Fédération Nationale des Centers de Lutte Contre le Cancer (FNCLCC) histopathological grading system. The correlation of the radiomic features and the FNCLCC grades was evaluated. We used the features correlated with the histopathological grades to build a model for predicting high-grade STS (Grade II and III).ResultsA total of 79 patients with STS were enrolled. And 15 radiomic features were found correlated with the FNCLCC grades of STSs, with the correlation coefficient ranging from 0.22 to 0.38. And 8 features showed significant difference among the three grades. The model for predicting high-grade STS based on the 8 radiomic features had an AUC value of 0.80, a sensitivity of 0.73, and a specificity of 0.78.ConclusionThe US radiomic features were correlated with the FNCLCC grade of STS. The radiomic analysis of US imaging could be potentially helpful for identifying the FNCLCC grades of STS pre-surgically.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1502613</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1502613</link>
        <title><![CDATA[Electroanatomic mapping reconstruction with photogrammetry across different mapping systems]]></title>
        <pubdate>2025-02-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Giacomo Talevi</author><author>Luigi Pannone</author><author>Domenico Giovanni Della Rocca</author><author>Antonio Sorgente</author><author>Rani Kronenberger</author><author>Ingrid Overeinder</author><author>Gezim Bala</author><author>Alexandre Almorad</author><author>Erwin Ströker</author><author>Juan Sieira</author><author>Mark La Meir</author><author>Andrea Sarkozy</author><author>Pedro Brugada</author><author>Gian Battista Chierchia</author><author>Ali Gharaviri</author><author>Carlo de Asmundis</author>
        <description><![CDATA[BackgroundAutomatic digital photogrammetry produces digital reproductions of objects using photographs. The aim of this study is to analyze feasibility of photogrammetry for electroanatomic map (EAM) reconstruction from different mapping systems. Furthermore, the possibility to import the reconstructed EAMs in a common working space is evaluated.MethodsAll consecutive patients undergoing EAM with one of the following EAM systems were screened for the study: (1) CARTO™; (2) Ensite™ X; (3) Rhythmia™; (4) Affera™ PRISM-3. All patient geometries were reconstructed from a video acquisition within the source EAM software. The video obtained was processed with Zephyr software and a dense point cloud was obtained. An image or sequence of images was selected to build a 3D mesh. At the end, the mesh was imported in the 3D graphics software Blender.ResultA total of 24 EAMs from 24 patients were included in the study. All EAMs were reconstructed with success using photogrammetry from all 4 mapping systems assessed. The process time was ≈ 25 min. In particular, EAMs were as follows: left atrium (2 Carto; 2 Ensite; 5 Rhythmia; 2 Affera), right atrium (1 Carto; 6 Ensite; 3 Affera) and left ventricles (1 Carto; 2 Ensite). All the reconstructed EAMs were imported in Blender with success. They could be visualized in Blender and all the operations were allowed including moving EAMs in a common working space and EAMs overlap.ConclusionThis study demonstrated for the first time the possibility of realizing 3-D objects from digital video formats of different EAMs.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2025.1542128</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2025.1542128</link>
        <title><![CDATA[Vision transformers for automated detection of diabetic peripheral neuropathy in corneal confocal microscopy images]]></title>
        <pubdate>2025-02-03T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Chaima Ben Rabah</author><author>Ioannis N. Petropoulos</author><author>Rayaz A. Malik</author><author>Ahmed Serag</author>
        <description><![CDATA[Early detection and management of diabetic peripheral neuropathy (DPN) are critical to reducing associated morbidity and mortality. Corneal Confocal Microscopy (CCM) facilitates the imaging of corneal nerves to detect early and progressive nerve damage in DPN. However, its wider adoption has been limited by the subjectivity and time-intensive nature of manual nerve fiber quantification. This study investigates the diagnostic utility of state-of-the-art Vision Transformer (ViT) models for the binary classification of CCM images to distinguish between healthy controls and individuals with DPN. The ViT model's performance was also compared to ResNet50, a convolutional neural network (CNN) previously applied for DPN detection using CCM images. Using a dataset of approximately 700 CCM images, the ViT model achieved an AUC of 0.99, a sensitivity of 98%, a specificity of 92%, and an F1-score of 95%, outperforming previously reported methods. These findings highlight the potential of the ViT model as a reliable tool for CCM-based DPN diagnosis, eliminating the need for time-consuming manual image segmentation. Moreover, the results reinforce CCM's value as a non-invasive and precise imaging modality for detecting nerve damage, particularly in neuropathy-related conditions such as DPN.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1530335</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1530335</link>
        <title><![CDATA[Editorial: Horizons in imaging]]></title>
        <pubdate>2024-12-20T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Alessandro Piva</author><author>Lifu Zhang</author><author>Jinchang Ren</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1478783</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1478783</link>
        <title><![CDATA[Presentation Attack Detection using iris periocular visual spectrum images]]></title>
        <pubdate>2024-12-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Andrés Valenzuela</author><author>Juan E. Tapia</author><author>Violeta Chang</author><author>Christoph Busch</author>
        <description><![CDATA[In this work, we analyse the comparison between using the periocular area instead of the full face area for Presentation Attack Detection (PAD) in the visual spectrum (RGB). The analysis was carried out by evaluating the performance of five Convolutional Neural Networks (CNN) using both facial and periocular iris images for PAD with two different attack instruments. Additionally, we improved the CNN results by integrating the ArcFace loss function instead of the traditional categorical cross-entropy loss, highlighting that the ArcFace function enhances the performance of the models for both regions of interest, facial and iris periocular areas. We conducted Binary and Multiclass comparisons, followed by cross-database validation to assess the generalization capabilities of the trained models. Our study also addresses some of the current challenges in PAD research, such as the limited availability of high-quality face datasets in the desired spectrum (RGB), which impacts the quality of Presentation Attack Instruments (PAI) examples used in training and evaluation. Our goal was to address the challenge of detecting Iris periocular presentation attacks by leveraging the ArcFace function. The results demonstrate the effectiveness of our approach and provide valuable insights for improving PAD systems using periocular areas in the visual spectrum.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1443142</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1443142</link>
        <title><![CDATA[Video tracking of single cells to identify clustering behavior]]></title>
        <pubdate>2024-12-02T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Mónica Suárez Korsnes</author><author>Håkon André Ramberg</author><author>Kristin Austlid Taskén</author><author>Reinert Korsnes</author>
        <description><![CDATA[Cancer cell clustering is a critical factor in metastasis, with cells often believed to migrate in groups as they establish themselves in new environments. This study presents preliminary findings from an in vitro experiment, suggesting that co-culturing cells provides an effective method for observing this phenomenon, even though the cells are grown as monolayers. We introduce a novel single-cell tracking approach based on graph theory to identify clusters in PC3 cells cultivated in both monoculture and co-culture with PC12 cells, using 66-h time-lapse recordings. The initial step consists of defining “linked” pairs of PC3 cells, laying the foundation for the application of graph theory. We propose two alternative definitions for cell pairings. The first method, Method 1, defines cells as “linked” at a given time t if they are close together within a defined time period before and after t. A second potential alternative method, Method 2, pairs cells if there is an overlap between the convex hulls of their respective tracks during this time period. Pairing cells enables the application of graph theory for subsequent analysis. This framework represents a cell as a vertex (node) and a relation between two cells as an edge. An interconnected set of high-degree nodes (nodes with many connections or edges) forms a subgraph, or backbone, that defines a patch (cluster) of cells. All nodes connected to this backbone are part of the subgraph. The backbone of high-degree nodes functions as a partition (or cut) of the initial graph. Two consecutive clusters in the video are considered to share the same identity if the following cluster contains at least p = 75 % of the cells from the preceding cluster, and the mean positions of their cells are within △r = 75μm. PC3 cells grown in co-culture appear to form persistent clusters exceeding 10 cells after 40–50 h incubation following seeding. In contrast, PC3 cells cultured alone (mono-culture) did not exhibit this behavior. This approach is experimental and requires further validation with a broader dataset.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1387543</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1387543</link>
        <title><![CDATA[Overhead fisheye cameras for indoor monitoring: challenges and recent progress]]></title>
        <pubdate>2024-09-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Janusz Konrad</author><author>Mertcan Cokbas</author><author>M. Ozan Tezcan</author><author>Prakash Ishwar</author>
        <description><![CDATA[Monitoring the number of people in various spaces of a building is important for optimizing space usage, assisting with public safety, and saving energy. Diverse approaches have been developed for different end goals, from ID card readers for space management, to surveillance cameras for security, to CO2 sensing for HVAC control. In the last few years, fisheye cameras mounted overhead have become the sensing modality of choice because they offer large-area coverage and significantly-reduced occlusions but research efforts are still nascent. In this paper, we provide an overview of recent research efforts in this area and propose one new direction. First, we identify benefits and challenges related to inference from top-view fisheye images, and summarize key public datasets. Then, we review efforts in algorithm development for detecting people from a single fisheye frame and from a group of sequential frames. Finally, we focus on counting people indoors. While this is straightforward for a single camera, when multiple cameras are used to monitor a space, person re-identification is needed to avoid overcounting. We describe a framework for people counting using two cameras and demonstrate its effectiveness in a large classroom for location-based person re-identification. To support people counting in even larger spaces, we propose two new person re-identification algorithms using N > 2 overhead fisheye cameras. We provide ample experimental results throughout the paper.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1418669</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1418669</link>
        <title><![CDATA[Growth independent morphometric machine learning workflow for single-cell antimicrobial susceptibility testing of Klebsiella pneumoniae to meropenem]]></title>
        <pubdate>2024-09-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kristel C. Tjandra</author><author>Nikhil Ram-Mohan</author><author>Manuel Roshardt</author><author>Elizabeth J. Zudock</author><author>Zhaonan Qu</author><author>Kathleen E. Mach</author><author>Okyaz Eminaga</author><author>Joseph C. Liao</author><author>Samuel Yang</author><author>Pak Kin Wong</author>
        <description><![CDATA[IntroductionMultidrug-resistant Enterobacteriaceae are among the most urgent global public health threats associated with various life-threatening infections. In the absence of a rapid method to identify antimicrobial susceptibility, empirical use of broad-spectrum antimicrobials such as carbapenem monotherapy has led to the spread of resistant organisms. Rapid determination of antimicrobial resistance is urgently needed to overcome this issue.MethodsBy capturing dynamic single-cell morphological features, including growth-independent, antibiotic-induced changes, of cells from 19 strains of Klebsiella pneumoniae, we evaluated data processing strategies based on time and concentration differentials to develop models for classifying its susceptibility to a commonly used carbapenem, meropenem, and predicting their minimum inhibitory concentrations (MIC).Results and discussionWe report morphometric antimicrobial susceptibility testing (MorphoAST), a growth independent, computer vision-based machine learning workflow, for rapid determination of antimicrobial susceptibility by single-cell morphological analysis within sub-doubling time of K. pneumoniae. We demonstrated the technological feasibility of predicting MIC/antimicrobial susceptibility in a fraction of the bacterial doubling time (<50 min). The classifiers achieved as high as 97% accuracy in 20 min (two-fifths of the doubling time) and reached over 99% accuracy within 50 min (one doubling time) in predicting the antimicrobial response of the validation dataset. A regression model based on the concentration differential of individual cells from nineteen strains predicted the MIC with 100% categorical agreement and essential agreement for seven unseen strains, including two clinical samples from patients with urinary tract infections with different responsiveness to meropenem, within 50 min of treatment. The expansion of this innovation to other drug-bug combinations could have significant implications for the future development of rapid antimicrobial susceptibility testing.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1421979</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1421979</link>
        <title><![CDATA[Infrared thermography and computed tomography imaging for hind limb study after immobilization-induced disuse atrophy]]></title>
        <pubdate>2024-08-07T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Berenice Martínez-Gutiérrez</author><author>Karla P. García-Pelagio</author>
        <description><![CDATA[Immobilization for treatment after an injury can lead to disuse atrophy, resulting in reduced functionality and strength of the immobilized limb. In our study, we utilized infrared thermography (IR) and computed tomography (CT) ex vivo to assess both physiological and structural changes following hind limb immobilization in a young Wistar rat model. Twelve rats weighing 275 ± 30 g had their right hind limbs immobilized with a modified Thomas-splint for varying durations (3, 7, or 14 days). IR imaging using an infrared camera provided insight into limb temperature changes. For micro-CT, we implemented a stain-ethanol fixation method and a gray score which enabled us to visualize and quantify muscle alterations. Thermographic images showed an increase in temperature of up to 8% in the hind limb at supine position at 14 days due to the inflammatory process while micro-CT exhibited muscle shrinkage of 10 and 18% at 7 and 14 days, respectively. Our findings underscore the efficacy of IR and micro-CT as rapid and precise imaging modalities for detecting morphological shifts in muscle tissue, particularly in pathological conditions like atrophy.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fimag.2024.1416114</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fimag.2024.1416114</link>
        <title><![CDATA[Intra-video positive pairs in self-supervised learning for ultrasound]]></title>
        <pubdate>2024-06-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Blake VanBerlo</author><author>Alexander Wong</author><author>Jesse Hoey</author><author>Robert Arntfield</author>
        <description><![CDATA[IntroductionSelf-supervised learning (SSL) is a strategy for addressing the paucity of labelled data in medical imaging by learning representations from unlabelled images. Contrastive and non-contrastive SSL methods produce learned representations that are similar for pairs of related images. Such pairs are commonly constructed by randomly distorting the same image twice. The videographic nature of ultrasound offers flexibility for defining the similarity relationship between pairs of images.MethodsWe investigated the effect of utilizing proximal, distinct images from the same B-mode ultrasound video as pairs for SSL. Additionally, we introduced a sample weighting scheme that increases the weight of closer image pairs and demonstrated how it can be integrated into SSL objectives.ResultsNamed Intra-Video Positive Pairs (IVPP), the method surpassed previous ultrasound-specific contrastive learning methods' average test accuracy on COVID-19 classification with the POCUS dataset by ≥ 1.3%. Detailed investigations of IVPP's hyperparameters revealed that some combinations of IVPP hyperparameters can lead to improved or worsened performance, depending on the downstream task.DiscussionGuidelines for practitioners were synthesized based on the results, such as the merit of IVPP with task-specific hyperparameters, and the improved performance of contrastive methods for ultrasound compared to non-contrastive counterparts.]]></description>
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