Computational cytology is a critical, rapid-developing, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …

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 …

Technical advancements significantly improve earlier diagnosis of cervical cancer, but
accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence …

With the development of machine learning and deep learning models, artificial intelligence
is now being applied to the field of medicine. In oncology, the use of artificial intelligence for …

Nowadays, deep learning (DL) is a popular tool used in various applications in different
fields, including the medical domain. DL techniques can cope with several challenges …

Cervical cancer is one of the most common cancers in daily life. Early detection and
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …

Early detection of cancer is important to improve survival and reduce associated morbility.
Nowadays, there is no automatic classification process with enough accuracy to be …

Purpose To compare deep learning with radiologists when diagnosing uterine cervical
cancer on a single T2-weighted image. Methods This study included 418 patients (age …

Cytology is a low-cost and non-invasive diagnostic procedure employed to support the
diagnosis of a broad range of pathologies. Cells are harvested from tissues by aspiration or …

The survival rate of cervical cancer can be improved by the early screening. However, the
screening is a heavy task for pathologists. Thus, automatic cervical cell classification model …