activity
20182021
most citedEvaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

29 citations · 33 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV20211 cited

Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT

Simone Bendazzoli, Irene Brusini, Mehdi Astaraki +7

Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent. However, manual segmentation can be very…

cs.CV2020

Investigating and Exploiting Image Resolution for Transfer Learning-based Skin Lesion Classification

Amirreza Mahbod, Gerald Schaefer, Chunliang Wang +3

Skin cancer is among the most common cancer types. Dermoscopic image analysis improves the diagnostic accuracy for detection of malignant melanoma and other pigmented skin lesions…

eess.IV20203 cited

A deep learning-based pipeline for error detection and quality control of brain MRI segmentation results

Irene Brusini, Daniel Ferreira Padilla, José Barroso +4

Brain MRI segmentation results should always undergo a quality control (QC) process, since automatic segmentation tools can be prone to errors. In this work, we propose two deep le…

cs.CV201929 cited

Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

Xiahai Zhuang, Lei Li, Christian Payer +31

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable…

physics.med-ph2018

AVRA: Automatic Visual Ratings of Atrophy from MRI images using Recurrent Convolutional Neural Networks

Gustav Mårtensson, Daniel Ferreira, Lena Cavallin +4

Quantifying the degree of atrophy is done clinically by neuroradiologists following established visual rating scales. For these assessments to be reliable the rater requires substa…