1 citations · 2 across the 7 of their papers we have counts for
8 papers
Lessons learned from deploying imaging AI with the open PACS-AI platform
Samuel Kadoury, Julie G. Hussin, Pascal Thériault-Lauzier +11
We describe deploying imaging AI at six hospitals through PACS-AI, an open self-hosted platform. The binding constraint is not model accuracy but infrastructure to route studies, d…
AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer
Gautier Hénique, William Le, Gabriel Dayan +8
Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is currently omitted as a clinical stag…
Few-Shot, Now for Real: Medical VLMs Adaptation without Balanced Sets or Validation
Julio Silva-Rodríguez, Fereshteh Shakeri, Houda Bahig +2
Vision-language models (VLMs) are gaining attention in medical image analysis. These are pre-trained on large, heterogeneous data sources, yielding rich and transferable representa…
Few-shot Adaptation of Medical Vision-Language Models
Fereshteh Shakeri, Yunshi Huang, Julio Silva-Rodríguez +4
Integrating image and text data through multi-modal learning has emerged as a new approach in medical imaging research, following its successful deployment in computer vision. Whil…
Boosting Vision-Language Models for Histopathology Classification: Predict all at once
Maxime Zanella, Fereshteh Shakeri, Yunshi Huang +2
The development of vision-language models (VLMs) for histo-pathology has shown promising new usages and zero-shot performances. However, current approaches, which decompose large s…
LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP
Yunshi Huang, Fereshteh Shakeri, Jose Dolz +3
In a recent, strongly emergent literature on few-shot CLIP adaptation, Linear Probe (LP) has been often reported as a weak baseline. This has motivated intensive research building…
Comparing 3D deformations between longitudinal daily CBCT acquisitions using CNN for head and neck radiotherapy toxicity prediction
William Trung Le, Chulmin Bang, Philippine Cordelle +4
Adaptive radiotherapy is a growing field of study in cancer treatment due to it's objective in sparing healthy tissue. The standard of care in several institutions includes longitu…
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!
Hoel Kervadec, Houda Bahig, Laurent Letourneau-Guillon +2
Standard losses for training deep segmentation networks could be seen as individual classifications of pixels, instead of supervising the global shape of the predicted segmentation…