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04/18/2023
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
Extent of resection after surgery is one of the main prognostic factors ...
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11/28/2022
Train smarter, not harder: learning deep abdominal CT registration on scarce data
Purpose: This study aims to explore training strategies to improve convo...
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12/21/2021
Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation
Purpose: Automating tasks such as lung tumor localization and segmentati...
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12/07/2021
Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images
Histopathological cancer diagnostics has become more complex, and the in...
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11/16/2021
Code-free development and deployment of deep segmentation models for digital pathology
Application of deep learning on histopathological whole slide images (WS...
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02/11/2021
Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding
As lung cancer evolves, the presence of enlarged and potentially maligna...
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01/19/2021
Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms
Meningiomas are the most common type of primary brain tumor, accounting ...
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11/11/2020
FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology
Deep convolutional neural networks (CNNs) are the current state-of-the-a...
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10/14/2020
