Detecting mitosis from cell population is a fundamental problem in many biological
researches and biomedical applications. In modern researches, advanced imaging …

We present an approach to jointly detect mitotic events spatially and temporally in time-lapse
phase contrast microscopy images. In particular, we combine a convolutional neural network …

In this paper, we report the results of the first international contest on mitosis detection in
phase-contrast microscopy image sequences (https://www. iti-tju. org/mitosisdetection) …

We propose a semi-Markov model trained in a max-margin learning framework for mitosis
event segmentation in large-scale time-lapse phase contrast microscopy image sequences …

We propose a fully-automated mitosis event detector using hidden conditional random fields
for cell populations imaged with time-lapse phase contrast microscopy. The method consists …

In this paper, we propose a straightforward and effective method for mitotic event detection
in time-lapse phase contrast microscopy image sequences of stem cell populations …

The analysis of cell mitotic behavior plays important role in many biomedical research and
medical diagnostic applications. To improve the accuracy of mitosis detection in automated …

Indirect immunofluorescence is the recommended method to detect autoantibodies in
patient serum, which could cause connective tissue diseases. One step of the diagnostic …

This paper proposes a multi-grained random fields (MGRFs) model for mitosis identification.
To deal with the difficulty in hidden state discovery and sequential structure modeling in …

In this paper, we solve the problem of mitosis event localization and its stage localization in
time-lapse phase-contrast microscopy images. Our method contains three steps: first, we …