activity
20192025
most citedThe Medical Segmentation Decathlon

1.3k citations · 2.1k across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imaging

Dashti A. Ali, Richard K. G. Do, William R. Jarnagin +2

In medical image analysis, feature engineering plays an important role in the design and performance of machine learning models. Persistent homology (PH), from the field of topolog…

eess.IV2023★ 1 cited

Comparing Regularized Kelvinlet Functions and the Finite Element Method for Registration of Medical Images to Sparse Organ Data

Morgan Ringel, Jon Heiselman, Winona Richey +3

Image-guided surgery collocates patient-specific data with the physical environment to facilitate surgical decision making in real-time. Unfortunately, these guidance systems commo…

eess.IV2021★ 1.3k cited

The Medical Segmentation Decathlon

Michela Antonelli, Annika Reinke, Spyridon Bakas +55

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely inv…

cs.CV2021★ 1 cited

EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting

Hassan Muhammad, Chensu Xie, Carlie S. Sigel +5

Histopathology-based survival modelling has two major hurdles. Firstly, a well-performing survival model has minimal clinical application if it does not contribute to the stratific…

cs.CV2019★ 10 cited

Towards Unsupervised Cancer Subtyping: Predicting Prognosis Using A Histologic Visual Dictionary

Hassan Muhammad, Carlie S. Sigel, Gabriele Campanella +9

Unlike common cancers, such as those of the prostate and breast, tumor grading in rare cancers is difficult and largely undefined because of small sample sizes, the sheer volume of…

cs.CV2019★ 718 cited

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Amber L. Simpson, Michela Antonelli, Spyridon Bakas +21

Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is c…