A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
Lymphocyte detection for cancer analysis using a novel fusion block based channel boosted CNN
Tumor-infiltrating lymphocytes, specialized immune cells, are considered an important
biomarker in cancer analysis. Automated lymphocyte detection is challenging due to its …
biomarker in cancer analysis. Automated lymphocyte detection is challenging due to its …
Coronavirus disease analysis using chest X-ray images and a novel deep convolutional neural network
Background The recent emergence of a highly infectious and contagious respiratory viral
disease known as COVID-19 has vastly impacted human lives and overloaded the health …
disease known as COVID-19 has vastly impacted human lives and overloaded the health …
Primary ovarian leiomyosarcoma is a very rare entity: a narrative review of the literature
VD Mandato, F Torricelli, V Mastrofilippo, A Palicelli… - Cancers, 2023 - mdpi.com
Simple Summary Primary ovarian leiomyosarcoma (POLMS) is a very rare malignancy
characterized by unclear management and poor survival. We reviewed all 113 cases of …
characterized by unclear management and poor survival. We reviewed all 113 cases of …
Detection of tumour infiltrating lymphocytes in CD3 and CD8 stained histopathological images using a two-phase deep CNN
Background Immuno-score, a prognostic measure for cancer, employed in determining
tumor grade and type, is generated by counting the number of Tumour-Infiltrating …
tumor grade and type, is generated by counting the number of Tumour-Infiltrating …
[HTML][HTML] SMDetector: Small mitotic detector in histopathology images using faster R-CNN with dilated convolutions in backbone model
Breast cancer is one of the most common cancer types among women, and it is a deadly
disease caused by the uncontrolled proliferation of cells. Pathologists face a challenging …
disease caused by the uncontrolled proliferation of cells. Pathologists face a challenging …
A review of computer-aided expert systems for breast cancer diagnosis
Simple Summary Breast cancer is one of the most commonly diagnosed diseases in females
around the world. The most threatening is when cancer spreads uncontrollably to other parts …
around the world. The most threatening is when cancer spreads uncontrollably to other parts …
Modality specific CBAM-VGGNet model for the classification of breast histopathology images via transfer learning
Histopathology images are very distinctive, one image may contain thousands of objects.
Transferring features from natural images to histopathology images may not provide …
Transferring features from natural images to histopathology images may not provide …
A novel breast cancer detection system using SDM-WHO-RNN classifier with LS-CED segmentation
GR Paul, J Preethi - Expert Systems with Applications, 2024 - Elsevier
Breast cancer (BC) is caused by the abnormal and rapid growth of breast cells. Accurate
diagnosis of BC at an early stage could minimize the mortality related to this disease …
diagnosis of BC at an early stage could minimize the mortality related to this disease …
Shuffled shepherd deer hunting optimization based deep neural network for breast cancer classification using breast histopathology images
DP Bhausaheb, KL Kashyap - Biomedical Signal Processing and Control, 2023 - Elsevier
Accurate classification of breast cancer from the histopathology images poses a difficult task
because of various benign breast tissue proliferative lesions and heterogeneity of abnormal …
because of various benign breast tissue proliferative lesions and heterogeneity of abnormal …