Multi-scale fully convolutional neural networks for histopathology image segmentation: from nuclear aberrations to the global tissue architecture

24 September 2019

Papers citing "Multi-scale fully convolutional neural networks for histopathology image segmentation: from nuclear aberrations to the global tissue architecture"

6 / 6 papers shown

Title
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps Sidi Wu Yizi Chen Konrad Schindler L. Hurni 19 2 0 19 Oct 2023
OCELOT: Overlapped Cell on Tissue Dataset for Histopathology Jeongun Ryu Aaron Valero Puche Jaewoong Shin Seonwook Park Biagio Brattoli ... S. Cho K. Paeng C-Y. Ock D. Yoo Sérgio Pereira 31 23 0 23 Mar 2023
A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images Hao Wang E. Ahn Jinman Kim 28 7 0 20 Mar 2023
Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathology Oliver Ester Fabian Horst C. Seibold J. Keyl Saskia Ting ... P. Ivanyi Viktor Grünwald J. Bräsen Jan Egger Jens Kleesiek 19 7 0 21 Oct 2022
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 280 10,613 0 19 Feb 2017
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 440 15,637 0 02 Nov 2015