Eugene Vorontsov
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Explore the profile of Eugene Vorontsov including associated specialties, affiliations and a list of published articles.
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12
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756
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Recent Articles
1.
de Boisredon dAssier M, Portafaix A, Vorontsov E, Le W, Kadoury S
Med Image Anal
. 2024 Aug;
97:103287.
PMID: 39111265
Deep neural networks are commonly used for automated medical image segmentation, but models will frequently struggle to generalize well across different imaging modalities. This issue is particularly problematic due to...
2.
Vorontsov E, Bozkurt A, Casson A, Shaikovski G, Zelechowski M, Severson K, et al.
Nat Med
. 2024 Jul;
30(10):2924-2935.
PMID: 39039250
The analysis of histopathology images with artificial intelligence aims to enable clinical decision support systems and precision medicine. The success of such applications depends on the ability to model the...
3.
Bilic P, Christ P, Li H, Vorontsov E, Ben-Cohen A, Kaissis G, et al.
Med Image Anal
. 2022 Dec;
84:102680.
PMID: 36481607
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI)...
4.
Vorontsov E, Molchanov P, Gazda M, Beckham C, Kautz J, Kadoury S
Med Image Anal
. 2022 Oct;
82:102624.
PMID: 36208571
An important challenge and limiting factor in deep learning methods for medical imaging segmentation is the lack of available of annotated data to properly train models. For the specific task...
5.
Antonelli M, Reinke A, Bakas S, Farahani K, Kopp-Schneider A, Landman B, et al.
Nat Commun
. 2022 Jul;
13(1):4128.
PMID: 35840566
International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have...
6.
Cros S, Bouttier H, Nguyen-Tan P, Vorontsov E, Kadoury S
J Appl Clin Med Phys
. 2022 Jun;
23(8):e13655.
PMID: 35661390
Purpose: External radiation therapy planning is a highly complex and tedious process as it involves treating large target volumes, prescribing several levels of doses, as well as avoiding irradiating critical...
7.
Le W, Vorontsov E, Romero F, Seddik L, Elsharief M, Nguyen-Tan P, et al.
Sci Rep
. 2022 Feb;
12(1):3183.
PMID: 35210482
In radiation oncology, predicting patient risk stratification allows specialization of therapy intensification as well as selecting between systemic and regional treatments, all of which helps to improve patient outcome and...
8.
Vorontsov E, Cerny M, Regnier P, Di Jorio L, Pal C, Lapointe R, et al.
Radiol Artif Intell
. 2021 May;
1(2):180014.
PMID: 33937787
Purpose: To evaluate the performance, agreement, and efficiency of a fully convolutional network (FCN) for liver lesion detection and segmentation at CT examinations in patients with colorectal liver metastases (CLMs)....
9.
Drozdzal M, Chartrand G, Vorontsov E, Shakeri M, Di Jorio L, Tang A, et al.
Med Image Anal
. 2017 Nov;
44:1-13.
PMID: 29169029
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets). We propose and examine...
10.
Chartrand G, Cheng P, Vorontsov E, Drozdzal M, Turcotte S, Pal C, et al.
Radiographics
. 2017 Nov;
37(7):2113-2131.
PMID: 29131760
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games....