Results 281 to 290 of about 4,840,174 (316)
Some of the next articles are maybe not open access.
Symmetry-based mitosis detection in time-lapse microscopy
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015Providing a general framework for mitosis detection is challenging. The variability of the visual traits and temporal features which classify the event of cell division is huge due to the numerous cell types, perturbations, imaging techniques and protocols used in microscopy imaging analysis studies.
Topaz Gilad +3 more
openaire +1 more source
A Domain Generalization Algorithm for Mitosis Detection Based on Local Feature Alignment
Proceedings of the 2024 International Conference on Biomedicine and Intelligent TechnologyMitosis detection is crucial for tumor diagnosis and prediction, yet, facing a domain shift challenge among different pathological images, which results in a poor generalization ability.
Huangrui Xiong, Ji Liu
semanticscholar +1 more source
Mitosis Detection from Breast Histopathology Images Using Mask RCNN
2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)Histopathology images are commonly used for cancer detection and prognosis as these images provide tissue level information which allow a pathologist to view the tumor cells and quantify them.
Aamina Taskeen +3 more
semanticscholar +1 more source
2024 9th International Conference on Computer Science and Engineering (UBMK)
Mitosis on H&E-stained (Hematoxylin and Eosin) images is an important prognostic marker for evaluating the tumor's aggressiveness and providing comprehensive and reliable information for accurate diagnosis and treatment.
Refik Samet +4 more
semanticscholar +1 more source
Mitosis on H&E-stained (Hematoxylin and Eosin) images is an important prognostic marker for evaluating the tumor's aggressiveness and providing comprehensive and reliable information for accurate diagnosis and treatment.
Refik Samet +4 more
semanticscholar +1 more source
Weakly supervised mitosis detection in breast histopathology images using concentric loss
Medical Image Anal., 2019HighlightsAn automatic and accurate system for detecting mitosis in histopathology images.Our method utilizes a deep segmentation network to produce segmentation map.
C. Li +5 more
semanticscholar +1 more source
Mitosis Detection for Invasive Breast Cancer Grading in Histopathological Images
IEEE Transactions on Image Processing, 2015Histopathological grading of cancer not only offers an insight to the patients' prognosis but also helps in making individual treatment plans. Mitosis counts in histopathological slides play a crucial role for invasive breast cancer grading using the Nottingham grading system.
Angshuman, Paul, Dipti Prasad, Mukherjee
openaire +2 more sources
Mitosis Detection in Multispectral Histopathological Images with Deep Learning
2019 Medical Technologies Congress (TIPTEKNO), 2019In this study, segmentation of cellular structures in the multispectral histopathological images and possibility of the discrimination within normal and mitotic cells have been investigated. In histopathological images, it is very challenging task to extract the mitotic cells from the histopathological image.
HAZRATOV, SARDOR, BİLGİN, Gökhan
openaire +2 more sources
ACNet: Aggregated Channels Network for Automated Mitosis Detection
2019Mitosis count is a critical predictor for invasive breast cancer grading using the Nottingham grading system. Nowadays mitotic count is mainly performed on high-power fields by pathologists manually under a microscope which is a highly tedious, time-consuming and subjective task. Therefore, it is necessary to develop automated mitosis detection methods
Kaili Cheng +5 more
openaire +1 more source
2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS), 2022
Lu Juei Min +8 more
openaire +1 more source
Lu Juei Min +8 more
openaire +1 more source