Results 31 to 40 of about 2,871,782 (268)
Keeping Pathologists in the Loop and an Adaptive F1-Score Threshold Method for Mitosis Detection in Canine Perivascular Wall Tumours [PDF]
CancersNicholas Bacon +2 more
exaly +2 more sources
A comparison of algorithms and humans for mitosis detection [PDF]
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 2014 We consider the problem of detecting mitotic figures in breast cancer histology slides. We investigate whether the performance of stateof-the-art detection algorithms is comparable to the performance of humans, when they are compared under fair conditions: our test subjects were not previously exposed to the task, and were required to learn their own ...
Alessandro Giusti +4 more
openaire +1 more source
Multi-task RetinaNet for Mitosis Detection
, 2023 The account of mitotic cells is a key feature in tumor diagnosis. However, due to the variability of mitotic cell morphology, it is a highly challenging task to detect mitotic cells in tumor tissues. At the same time, although advanced deep learning method have achieved great success in cell detection, the performance is often unsatisfactory when ...
Ziyue Wang 0005 +4 more
openaire +3 more sources
Sk-Unet Model with Fourier Domain for Mitosis Detection [PDF]
, 2022 Mitotic count is the most important morphological feature of breast cancer grading. Many deep learning-based methods have been proposed but suffer from domain shift. In this work, we construct a Fourier-based segmentation model for mitosis detection to address the problem.
Sen Yang 0006 +3 more
openaire +3 more sources
MitosisNet: End-to-End Mitotic Cell Detection by Multi-Task Learning
IEEE Access, 2020 Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis.
Md Zahangir Alom +4 more
doaj +1 more source
IEEE Access, 2020 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 figures from breast cancer histological slides using a ...
Meriem Sebai +2 more
doaj +1 more source
Spectral band selection for mitosis detection in histopathology [PDF]
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 2014 This study aims at evaluating the accuracy of mitosis detection on multispectral histopathological images by developing a solution specifically designed to take advantage of multispectral information. The proposed framework includes a selection of spectral bands and focal plane, detection of candidate mitotic regions, computation of morphological ...
Humayun Irshad +3 more
openaire +2 more sources
peggyscshu/Mitosis-phase-analysis:
, 2021 A cell cycle occurs as a cell divides. The somatic cell leaves interphase, undergoes mitosis and eventually gives out two daughter cells. Mitosis is composed by a series of events including prophase, metaphase, anaphase and telophase.
Shao-Chun, Peggy, Hsu
core +1 more source
Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method. [PDF]
PLoS ONE, 2016 Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer.
Mitko Veta +4 more
doaj +1 more source
Representation of Differential Learning Method for Mitosis Detection [PDF]
Journal of Healthcare Engineering, 2021 The breast cancer microscopy images acquire information about the patient’s ailment, and the automated mitotic cell detection outcomes have generally been utilized to ease the massive amount of pathologist’s work and help the pathologists make clinical decisions quickly.
Haider Ali +8 more
openaire +1 more source