most citedLocation Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

26 citations · 27 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI20245 cited

Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications

Daan Schouten, Giulia Nicoletti, Bas Dille +5

Recent technological advances in healthcare have led to unprecedented growth in patient data quantity and diversity. While artificial intelligence (AI) models have shown promising…

cs.CV2024

Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers

Clément Grisi, Geert Litjens, Jeroen van der Laak

Vision Transformers are at the heart of the current surge of interest in foundation models for histopathology. They process images by breaking them into smaller patches following a…

cs.CV20241 cited

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop

Nadieh Khalili, Joey Spronck, Francesco Ciompi +2

Deep learning algorithms, often critiqued for their 'black box' nature, traditionally fall short in providing the necessary transparency for trusted clinical use. This challenge is…

eess.IV20221 cited

Domain adaptation strategies for cancer-independent detection of lymph node metastases

Péter Bándi, Maschenka Balkenhol, Marcory van Dijk +3

Recently, large, high-quality public datasets have led to the development of convolutional neural networks that can detect lymph node metastases of breast cancer at the level of ex…

cs.CV201626 cited

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +7

The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in co…