The last decade has seen tremendous progress in quantitative imaging (aka Radiomics) methods and the explosive reinvention of neural networks in multi-scaled forms as deep networks with unprecedented industrial contribution towards open source tools. These developments have impacted all areas of society and more so to the medical imaging community. The innovations have instigated several questions for the research community to ponder on fair ethical use of technology, reliable, reproducible use of these AI/quantitative imaging methods in medicine. We would like the methods used by the community to be reliable and robust to the fullest extent possible and reproducible across various changes.
In this spirit, we would like to dedicate this Research Topic to invite exploration within the below areas (but not limited to). The articles can be original research, short commentary or a review on these topics.
? Reproducible radiomics methods in oncology
? Measure repeatability of AI/Radiomics methods in medical imaging
? Fair and ethical AI – impact or consequence in use of advanced imaging, AI methods to society.
? Survey on existing tools in AI or Radiomics in oncology.
? Limits or failure of AI/Radiomic methods
Topic Editor, Yoganand Balagurunathan has declared no competing interests with regard to the research topic subject. He has been associated with POP-test LLC, (Consultant/Advisor in Y2014-17) and Dexterity LLC, (Paid (freelance), Scientific consultant, in Y2011-12). Harini Veeraraghavan has declared no competing interests with regard to the Research Topic subject.
The last decade has seen tremendous progress in quantitative imaging (aka Radiomics) methods and the explosive reinvention of neural networks in multi-scaled forms as deep networks with unprecedented industrial contribution towards open source tools. These developments have impacted all areas of society and more so to the medical imaging community. The innovations have instigated several questions for the research community to ponder on fair ethical use of technology, reliable, reproducible use of these AI/quantitative imaging methods in medicine. We would like the methods used by the community to be reliable and robust to the fullest extent possible and reproducible across various changes.
In this spirit, we would like to dedicate this Research Topic to invite exploration within the below areas (but not limited to). The articles can be original research, short commentary or a review on these topics.
? Reproducible radiomics methods in oncology
? Measure repeatability of AI/Radiomics methods in medical imaging
? Fair and ethical AI – impact or consequence in use of advanced imaging, AI methods to society.
? Survey on existing tools in AI or Radiomics in oncology.
? Limits or failure of AI/Radiomic methods
Topic Editor, Yoganand Balagurunathan has declared no competing interests with regard to the research topic subject. He has been associated with POP-test LLC, (Consultant/Advisor in Y2014-17) and Dexterity LLC, (Paid (freelance), Scientific consultant, in Y2011-12). Harini Veeraraghavan has declared no competing interests with regard to the Research Topic subject.
