Abstract Background and Objective Early diagnosis and classification of a cancer type can
help facilitate the subsequent clinical management of the patient. Cervical cancer ranks as …

Computer aided categorization of smear images are considered as an open problem for a
last few decades. Cervical cancer is the main cause of mortality among women population …

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

Cervical cancer is one of the leading causes of cancer death in females worldwide. The
disease can be cured if the patient is diagnosed in the pre-cancerous lesion stage or earlier …

Background and objectives The present study proposes an intelligent system for automatic
categorization of Pap smear images to detect cervical dysplasia, which has been an open …

The Pap smear test is a manual screening procedure that is used to detect precancerous
changes in cervical cells based on color and shape properties of their nuclei and …

The purpose of this study is to develop an intelligent remote detection and diagnosis system
for breast cancer based on cytological images. First, this paper presents a fully automated …

Accurate nuclei segmentation, as an indispensable basis and core link for multi-cell cervical
image analysis, plays an important role in automatic pre-cancer detection. However, poor …

Pathological examination of microscopic image of Pap smear slide remains the main
method for cervical cancer diagnosis. The accurate segmentation and classification of …

The task of segmenting cell nuclei and cytoplasm in pap smear images is one of the most
challenging tasks in automated cervix cytological analysis due to specifically the presence of …