Centrosome‑, mitotic spindle‑ and cytokinetic bridge‑specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non‑canonical, RNAi‑dependent, control of local homeostasis. [PDF]
Mol Med RepTheotoki EI +7 more
europepmc +1 more source
Use of AI Histopathology in Breast Cancer Diagnosis. [PDF]
Medicina (Kaunas)Ivanov V +7 more
europepmc +1 more source
Targeting the splicing factor CWC22 induces mitotic slippage through repression of BubR1 expression and CDK1 activity in cancer cells. [PDF]
J Biol ChemYuki R, Saito Y, Nakayama Y.
europepmc +1 more source
GMCL1 controls 53BP1 stability and modulates taxane sensitivity. [PDF]
ElifeKito Y +9 more
europepmc +1 more source
Related searches:
An Improved Object Detection Method for Mitosis Detection
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019Breast cancer grading is important for patient prognosis, and the mitosis count is one of the most important indicators for breast cancer grading. Traditional methods use handcraft features and deep learning based methods to detect mitosis in a classified model. These methods are time-consuming and difficult for practical clinical practice application.
Haijun, Lei +4 more
openaire +2 more sources
Mitosis Detection Using Image Segmentation and Object Detection
2019 IEEE Conference on Information and Communication Technology, 2019The 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 +6 more
openaire +1 more source
DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
Medical Image Analysis, 2018Mitotic 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 +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, 2014Histopathological 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), 2017One 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 +3 more
openaire +1 more source
Mitosis detection using convolutional neural network based features
2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI), 2016Breast 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