Recent trends in computer assisted diagnosis (CAD) system for breast cancer diagnosis using histopathological images
Breast cancer is one of the common type of cancer in females across the world. An early
detection and diagnosis of breast cancer may reduce the mortality rate to a great extent. To …
detection and diagnosis of breast cancer may reduce the mortality rate to a great extent. To …
Mitosis detection techniques in H&E stained breast cancer pathological images: A comprehensive review
Quantifying mitosis in pathological sections is of great significance in the pathological
diagnosis of breast cancer as it is used to evaluate the aggressiveness of the tumor and to …
diagnosis of breast cancer as it is used to evaluate the aggressiveness of the tumor and to …
Artificial intelligence-based mitosis detection in breast cancer histopathology images using faster R-CNN and deep CNNs
Breast cancer is the leading cause of mortality in women. Early diagnosis of breast cancer
can reduce the mortality rate. In the diagnosis, the mitotic cell count is an important …
can reduce the mortality rate. In the diagnosis, the mitotic cell count is an important …
Efficient deep learning model for mitosis detection using breast histopathology images
Mitosis detection is one of the critical factors of cancer prognosis, carrying significant
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
Weakly supervised mitosis detection in breast histopathology images using concentric loss
Developing new deep learning methods for medical image analysis is a prevalent research
topic in machine learning. In this paper, we propose a deep learning scheme with a novel …
topic in machine learning. In this paper, we propose a deep learning scheme with a novel …
DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis.
Nowadays mitosis counting is mainly performed by pathologists manually, which is …
Nowadays mitosis counting is mainly performed by pathologists manually, which is …
Novel architecture with selected feature vector for effective classification of mitotic and non-mitotic cells in breast cancer histology images
The paper focuses on the detection of mitosis in breast cancer. Detection methods in vogue
rely heavily on visual inspection and assessment of histology images by trained …
rely heavily on visual inspection and assessment of histology images by trained …
MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images
Counting the mitotic cells in histopathological cancerous tissue areas is the most relevant
indicator of tumor grade in aggressive breast cancer diagnosis. In this paper, we propose a …
indicator of tumor grade in aggressive breast cancer diagnosis. In this paper, we propose a …
PartMitosis: a partially supervised deep learning framework for mitosis detection in breast cancer histopathology images
M Sebai, T Wang, SA Al-Fadhli - IEEE Access, 2020 - ieeexplore.ieee.org
Detection of mitotic tumor cells per tissue area is one of the critical markers of breast cancer
prognosis. The aim of this paper is to develop a method for the automatic detection of mitotic …
prognosis. The aim of this paper is to develop a method for the automatic detection of mitotic …
A survey on automated cancer diagnosis from histopathology images
J Angel Arul Jothi, V Mary Anita Rajam - Artificial Intelligence Review, 2017 - Springer
Detecting cancer at an early stage is useful in better patient prognosis and treatment
planning. Even though there are several preliminary tests and non-invasive procedures that …
planning. Even though there are several preliminary tests and non-invasive procedures that …