Results 251 to 260 of about 4,840,174 (316)

A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images

Medical Image Anal., 2022
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which supports disease prognostication and treatment planning. Developing a robust mitotic cell detection model is highly challenging due to its complex growth pattern and
Xiyue Wang, Jun Zhang, Sen Yang, Jin Xiang, Feng Luo, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang, Xiao Han   +9 more
semanticscholar   +1 more source

Mitosis Detection Using Image Segmentation and Object Detection

2019 IEEE Conference on Information and Communication Technology, 2019
The World Health Organisation(WHO) identifies that in women, the second most cancer deaths are caused by Breast cancer[1]. This paper presents various approaches for Mitosis detection on publicly available MITOS data set and DSB (Data Science Bowl). The process involves using a U-Net architecture consisting of convolution and deconvolution layers to ...
Nairit Banerjee, Anmol Singh Sethi, Manavdeep Singh, G. Srisha Anagh, Badnena SVVR Upendra, Artus Krohn-Grimberghe, Ranjana Vyas   +6 more
openaire   +1 more source

DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks

Medical Image Analysis, 2018
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 extremely arduous and time-consuming. In this paper, we propose an accurate method for detecting the mitotic cells from histopathological slides using a novel multi-stage deep ...
Chao, Li, Xinggang, Wang, Wenyu, Liu, Longin Jan, Latecki   +3 more
openaire   +2 more sources

Enhanced Random Forest for Mitosis Detection

Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing, 2014
Histopathological grading of cancer is a measure of the cell appearance in malignant neoplasms. Grading offers an insight to the growth of the cancer and helps in developing individual treatment plans. The Nottingham grading system [12], well known method for invasive breast cancer grading, primarily relies on the mitosis count in histopathological ...
Angshuman Paul, Dipti Prasad Mukherjee
openaire   +1 more source

Wide residual networks for mitosis detection

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017
One of the most important prognostic markers to assess proliferation activity of breast tumors is estimating the number of mitotic figures in H&E stained tissue. We propose the use of a recently published convolutional neural network architecture, Wide Residual Networks, for mitosis detection in breast histology images. The model is trained to classify
Erwan Zerhouni, David Lanyi, Matheus Viana, Maria Gabrani   +3 more
openaire   +1 more source

Mitosis Detection In Breast Histopathology Image Using Ensemble Features Fed CNN Model

International Conference on Computing Communication and Networking Technologies, 2023
Breast cancer is acknowledged as the second leading cause of women’s cancer-related deaths. Quantifying mitosis in pathology sections can provide invaluable insight into both the prognosis and tumor aggressiveness.
Anjana J. Suresh, L. S. Nair
semanticscholar   +1 more source

Rethinking mitosis detection: Towards diverse data and feature representation for better domain generalization

Artif. Intell. Medicine
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell.
Jiatai Lin, Hao Wang, Danyi Li, Jing Wang, Bingchao Zhao, Zhenwei Shi, Changhong Liang, Guoqiang Han, Li Liang, Zaiyi Liu, Chu Han   +10 more
semanticscholar   +1 more source

A deep learning approach for mitosis detection: Application in tumor proliferation prediction from whole slide images

Artif. Intell. Medicine, 2021
The tumor proliferation, which is correlated with tumor grade, is a crucial biomarker indicative of breast cancer patients' prognosis. The most commonly used method in predicting tumor proliferation speed is the counting of mitotic figures in Hematoxylin
R. Nateghi, H. Danyali, M. Helfroush
semanticscholar   +1 more source

Mitosis detection using convolutional neural network based features

2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI), 2016
Breast cancer is the second leading cause of cancer death in women according to World Health Organization (WHO). Development of computer aided diagnostic (CAD) systems has great importance as a secondary reader systems for a correct diagnosis and treatment process.
BİLGİN, Gökhan, Albayrak, Abdulkadir
openaire   +2 more sources

An interpretable machine learning framework for automated mitosis detection in gastrointestinal stromal tumors.

Pathology, Research and Practice
The mitotic index is a critical indicator in grading gastrointestinal stromal tumors (GIST). Conventional microscopy-based mitosis counting is labor-intensive and exhibits interobserver variability, necessitating automation. However, existing models have
Xin Dong, Jiaqiang Dong, Kai Liu, M. Niu, Yue Wang, L. Miao, Y. Zhe, Ying Han, Zhiguo Liu   +8 more
semanticscholar   +1 more source