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researcher

A. Tucholka

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • eess.IV3

identity via Semantic Scholar / OpenAlex

most citedTrustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis

13 citations · 13 across the 2 of their papers we have counts for

collaborators

3 papers

eess.IV2022★ 13 cited

Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis

Benjamin Lambert, Florence Forbes, Alan Tucholka +3

The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature. Particula…

eess.IV2022

Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust

Benjamin Lambert, Florence Forbes, Senan Doyle +2

Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images. Their full acceptance by clinicians remains however hampered by the…

eess.IV2021

Leveraging 3D Information in Unsupervised Brain MRI Segmentation

Benjamin Lambert, Maxime Louis, Senan Doyle +3

Automatic segmentation of brain abnormalities is challenging, as they vary considerably from one pathology to another. Current methods are supervised and require numerous annotated…

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