Objective: The likelihood of timely treatment for cervical cancer increases with timely
detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells …

Pathology image analysis is an essential procedure for clinical diagnosis of numerous
diseases. To boost the accuracy and objectivity of the diagnosis, nowadays, an increasing …

In this paper, we develop a new weakly supervised learning algorithm to learn to segment
cancerous regions in histopathology images. This paper is under a multiple instance …

Labeling a histopathology image as having cancerous regions or not is a critical task in
cancer diagnosis; it is also clinically important to segment the cancer tissues and cluster …

Colposcopy is currently a common medical technique for preventing cervical cancer.
However, with the increase of the workload, screening by artificial vision has the problems of …

Cancer tissues in histopathology images exhibit abnormal patterns; it is of great clinical
importance to label a histopathology image as having cancerous regions or not and perform …

Cervical cancer is one of the most common gynecological malignancies, and when detected
and treated at an early stage, the cure rate is almost 100%. Colposcopy can be used to …

Background The intersection of artificial intelligence (AI) with cancer research is increasing,
and many of the advances have focused on the analysis of cancer images. Objectives To …

Detecting cancer at an early stage is useful in better patient prognosis and treatment
planning. Even though there are several preliminary tests and non-invasive procedures that …

Cervical cancer is the second most common type of cancer for women. Existing screening
programs for cervical cancer, such as Pap Smear, suffer from low sensitivity. Thus, many …