- Grand Challenge

Tejas S Gowda

T3JA5

India
National Institute of Technology Karnataka
Computer Science and Engineering
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Member for 2 months

Activity Overview

Decathlon

Challenge User

The Medical Segmentation Decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.

PUMA: Panoptic segmentation of nUclei and tissue in MelanomA

Challenge User

The PUMA Challenge aims to enhance nuclei and tissue segmentation in melanoma histopathology, addressing the need for better prognostic biomarkers to predict treatment responses. Melanoma, a highly aggressive skin cancer, often requires immune checkpoint inhibition therapy, but only half of patients respond. Prognostic biomarkers like tumor infiltrating lymphocytes (TILs) correlate with better therapy responses and lower recurrence rate, but manual TIL scoring is subjective and inconsistent. Current deep learning methods underperform. The PUMA dataset includes annotated primary and metastatic melanoma regions to improve segmentation techniques. The challenge includes two tracks with tasks focused on tissue and nuclei segmentation, encouraging advanced methods to improve predictive accuracy.