Validation metrics are key for tracking scientific progress and bridging the current chasm
between artificial intelligence research and its translation into practice. However, increasing …

Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …

International challenges have become the de facto standard for comparative assessment of
image analysis algorithms. Although segmentation is the most widely investigated medical …

Automatic segmentation of abdominal organs in CT scans plays an important role in clinical
practice. However, most existing benchmarks and datasets only focus on segmentation …

This paper relates the post-analysis of the first edition of the HEad and neCK TumOR
(HECKTOR) challenge. This challenge was held as a satellite event of the 23rd International …

Recent advances in transformer-based models have drawn attention to exploring these
techniques in medical image segmentation, especially in conjunction with the U-Net model …

While the importance of automatic image analysis is continuously increasing, recent meta-
research revealed major flaws with respect to algorithm validation. Performance metrics are …

In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …

Detection and segmentation of abnormalities on medical images is highly important for
patient management including diagnosis, radiotherapy, response evaluation, as well as for …

Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst
most polyps are benign, the polyp's number, size and surface structure are linked to the risk …