In this paper, a superpixel and convolution neural network (CNN) based segmentation
method is proposed for cervical cancer cell segmentation. Since the background and …

In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based
method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically …

The task of segmenting cytoplasm in cytology images is one of the most challenging tasks in
cervix cytological analysis due to the presence of fuzzy and highly overlapping cells. Deep …

Cervical nuclei carry substantial diagnostic information for cervical cancer. Therefore, in
automation-assisted reading of cervical cytology, automated and accurate segmentation of …

Segmentation of cervical cells in microscopic images is an important task for computer-aided
diagnosis of cervical cancer. However, their segmentation is challenging due to …

Accurate cell segmentation is essential for computer-aided diagnosis of cervical
precancerous lesions in cytology images. Automated segmentation poses a great challenge …

Background: Advances in image analysis and computational techniques have facilitated
automatic detection of critical features in histopathology images. Detection of nuclei is critical …

Cervical cancer is the fourth most prevalent disease in women. Accurate and timely cancer
detection can save lives. Automatic and reliable cervical cancer detection methods can be …

In the screening of cervical cancer cells, accurate identification and segmentation of nucleus
in cell images is a key part in the early diagnosis of cervical cancer. Overlapping, uneven …

Precise segmentation of Pap smear cell nucleus is crucial for early diagnosis of cervical
cancer. This task is particularly challenging because of cell overlapping, inconsistent …