activity
20122020
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 751 across the 5 of their papers we have counts for

collaborators

6 papers

physics.med-ph202011 cited

A radiomics approach to analyze cardiac alterations in hypertension

Irem Cetin, Steffen E. Petersen, Sandy Napel +3

Hypertension is a medical condition that is well-established as a risk factor for many major diseases. For example, it can cause alterations in the cardiac structure and function o…

math.ST2020

A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions

Masoud Badiei Khuzani, Yinyu Ye, Sandy Napel +1

We develop and analyze a projected particle Langevin optimization method to learn the distribution in the Schönberg integral representation of the radial basis functions from train…

eess.IV201922 cited

A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI

Irem Cetin, Gerard Sanroma, Steffen E. Petersen +4

Use expert visualization or conventional clinical indices can lack accuracy for borderline classications. Advanced statistical approaches based on eigen-decomposition have been mos…

cs.CV2019718 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…

cs.CV2016

Adaptive Local Window for Level Set Segmentation of CT and MRI Liver Lesions

Assaf Hoogi, Christopher F. Beaulieu, Guilherme M. Cunha +4

We propose a novel method, the adaptive local window, for improving level set segmentation technique. The window is estimated separately for each contour point, over iterations of…

cs.LG2012

A Hybrid Method for Distance Metric Learning

Yi-Hao Kao, Benjamin Van Roy, Daniel Rubin +3

We consider the problem of learning a measure of distance among vectors in a feature space and propose a hybrid method that simultaneously learns from similarity ratings assigned t…