Jose Dolz
Associate Professor
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolJose Dolz is an associate professor and computer vision researcher with nine years of experience applying deep learning to medical image segmentation, particularly for organs-at-risk in radiotherapy and oncology. After engineering studies in Spain, he combined industry R&D—building AR, tracking and pose-estimation systems—with Marie Curie-funded PhD and postdoc work that fused hybrid segmentation and regularization techniques. At École de technologie supérieure in Montreal he leads research on CNN-based methods that integrate classical constraints to push state-of-the-art performance in clinical applications. His background building deployable vision products gives him a practical edge in translating algorithms into usable tools for healthcare. He is known for bridging signal-processing roots with modern deep learning to address persistent clinical segmentation challenges.
10 years of coding experience
7 years of employment as a software developer
Bachelor and M.Sc.Degree, Telecommunications, Image Processing, Bachelor and M.Sc.Degree, Telecommunications, Image Processing at Polytechnic University of ValenciaDoctor of Philosophy (PhD), Medical Imaging, Summa Cum Laude, Doctor of Philosophy (PhD), Medical Imaging, Summa Cum Laude at Ecole Doctorale Biologie SantéM.Sc. Student, Telecommunications & Radio Engineering focusing in Signal Processing, M.Sc. Student, Telecommunications & Radio Engineering focusing in Signal Processing at Högskolan i Gävle
Spanish, English, French, German
Stackoverflow
1reputation
0reached
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Github Skills (36)
convolutional-neural-networks10
medical-image-processing10
biomedical-image-analysis10
attention-mechanism10
encoder-decoder10
unet-image-segmentation10
image-segmentation10
densenet10
deep-learning10
segmentation10
medical-image-analysis10
neuroimaging10
3d10
medical-imaging10
medical-image-segmentation10
Programming languages (2)
Github contributions (5)
josedolz/SemiDenseNet
Oct 2017 - Dec 2017
Repository containing the code of one of the networks that we employed in the iSEG Grand MICCAI Challenge 2017, infant brain segmentation.
Contributions:29 commits, 29 pushes, 1 branch in 1 month
segmentation3dcnntheanoconvolutional-neural-networks
sinAshish/Multi-Scale-Attention
Jun 2019 - Apr 2020
[JBHI] Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Contributions:19 commits, 19 pushes, 12 comments in 10 months
medical-image-segmentationpytorchdeep-learningbiomedical-image-analysisattention-mechanism
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