Search Results for author:
Found 7 papers, 5 papers with code
Immunohistochemistry guided segmentation of benign epithelial cells, in situ lesions, and invasive epithelial cells in breast cancer slides
In this study, we aimed to develop an AI model for segmentation of epithelial cells in sections from breast cancer.
Towards Robust Cardiac Segmentation using Graph Convolutional Networks
We propose a graph architecture that uses two convolutional rings based on cardiac anatomy and show that this eliminates anatomical incorrect multi-structure segmentations on the publicly available CAMUS dataset.
Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images
To validate the design, we conducted an ablation study to assess the impact of selected components in the pipeline on tumour segmentation.
Code-free development and deployment of deep segmentation models for digital pathology
Application of deep learning on histopathological whole slide images (WSIs) holds promise of improving diagnostic efficiency and reproducibility but is largely dependent on the ability to write computer code or purchase commercial solutions.
FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology
It minimizes memory usage for reading and processing WSIs, deployment of CNN models, and real-time interactive visualization of results.
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography
Results obtained on a large open access dataset show that our method outperforms the current best performing deep learning solution and achieved an overall segmentation accuracy lower than the intra-observer variability for the epicardial border (i. e. on average a mean absolute error of 1. 5mm and a Hausdorff distance of 5. 1mm) with 11% of outliers.
Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis.
