PFA-ScanNet: Pyramidal feature aggregation with synergistic learning for breast cancer metastasis analysis
Automatic detection of cancer metastasis from whole slide images (WSIs) is a crucial step for
following patient staging and prognosis. Recent convolutional neural network based …
following patient staging and prognosis. Recent convolutional neural network based …
Deep learning for detecting breast cancer metastases on WSI
K Fan, S Wen, Z Deng - Innovation in Medicine and Healthcare Systems …, 2019 - Springer
Pathologists face a substantial increase in workload and complexity of histopathologic
cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic …
cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic …
Scannet: A fast and dense scanning framework for metastastic breast cancer detection from whole-slide image
Lymph node metastasis is one of the most significant diagnostic indicators in breast cancer,
which is traditionally observed under the microscope by pathologists. In recent years …
which is traditionally observed under the microscope by pathologists. In recent years …
Fast scannet: Fast and dense analysis of multi-gigapixel whole-slide images for cancer metastasis detection
Lymph node metastasis is one of the most important indicators in breast cancer diagnosis,
that is traditionally observed under the microscope by pathologists. In recent years, with the …
that is traditionally observed under the microscope by pathologists. In recent years, with the …
Cancer metastasis detection with neural conditional random field
Breast cancer diagnosis often requires accurate detection of metastasis in lymph nodes
through Whole-slide Images (WSIs). Recent advances in deep convolutional neural …
through Whole-slide Images (WSIs). Recent advances in deep convolutional neural …
Se-densenet: attention-based network for detecting pathological images of metastatic breast cancer
Y Duan, L Sun, Y Wang - Proceedings of the 2019 8th International …, 2019 - dl.acm.org
Clinically, the doctor judges the degree of tumor infiltration, and identifies whether it is
metastasized by observing the histopathological section of the patient, and conducts …
metastasized by observing the histopathological section of the patient, and conducts …
Cancer metastasis detection through multiple spatial context network
W Zhang, C Zhu, J Liu, Y Wang, M Jin - Proceedings of the 2019 8th …, 2019 - dl.acm.org
Breast cancer is one of the leading causes of death by cancer in women, and it often
requires accurate detection of metastasis in lymph nodes through Whole-slide Images …
requires accurate detection of metastasis in lymph nodes through Whole-slide Images …
Boosted efficientnet: Detection of lymph node metastases in breast cancer using convolutional neural networks
Simple Summary The assistance of computer image analysis that automatically identifies
tissue or cell types has greatly improved histopathologic interpretation and diagnosis …
tissue or cell types has greatly improved histopathologic interpretation and diagnosis …
Pathtr: Context-aware memory transformer for tumor localization in gigapixel pathology images
With the development of deep learning and computation pathology, whole-slide images
(WSIs) are wildly used in clinical diagnosis. The WSI, which refers to the scanning of …
(WSIs) are wildly used in clinical diagnosis. The WSI, which refers to the scanning of …
A robust and effective approach towards accurate metastasis detection and pn-stage classification in breast cancer
B Lee, K Paeng - Medical Image Computing and Computer Assisted …, 2018 - Springer
Predicting TNM stage is the major determinant of breast cancer prognosis and treatment.
The essential part of TNM stage classification is whether the cancer has metastasized to the …
The essential part of TNM stage classification is whether the cancer has metastasized to the …