192 citations · 314 across the 20 of their papers we have counts for
23 papers
Quality-Guided Semi-Supervised Learning for Medical Image Segmentation
Kumar Abhishek, Ghassan Hamarneh
Training accurate medical image segmentation models requires large amounts of densely annotated data, which is costly and time-consuming to obtain. Semi-supervised learning (SSL) a…
IMA++: ISIC Archive Multi-Annotator Dermoscopic Skin Lesion Segmentation Dataset
Kumar Abhishek, Jeremy Kawahara, Ghassan Hamarneh
Multi-annotator medical image segmentation is an important research problem, but requires annotated datasets that are expensive to collect. Dermoscopic skin lesion imaging allows h…
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
Kumar Abhishek, Jeremy Kawahara, Ghassan Hamarneh
Medical image segmentation exhibits intra- and inter-annotator variability due to ambiguous object boundaries, annotator preferences, expertise, and tools, among other factors. Les…
Ethical Medical Image Synthesis
Weina Jin, Ashish Sinha, Kumar Abhishek +1
The task of ethical Medical Image Synthesis (MISyn) is to ensure that the MISyn techniques are researched and developed ethically throughout their entire lifecycle, which is essent…
Disentangled PET Lesion Segmentation
Tanya Gatsak, Kumar Abhishek, Hanene Ben Yedder +2
PET imaging is an invaluable tool in clinical settings as it captures the functional activity of both healthy anatomy and cancerous lesions. Developing automatic lesion segmentatio…
Lesion Elevation Prediction from Skin Images Improves Diagnosis
Kumar Abhishek, Ghassan Hamarneh
While deep learning-based computer-aided diagnosis for skin lesion image analysis is approaching dermatologists' performance levels, there are several works showing that incorporat…