Image processing has enabled faster and more accurate image classification. It has been of
great benefit to the health industry. Manually examining medical images like MRI and X‐rays …

Cervical cancer is a significant contributor to female mortality on a global scale, especially in
low-income countries where effective screening programs for the detection and treatment of …

Detecting and classifying the Pap smear cell images is important task for cervical cancer
identification. In this article, dual tree complex wavelet transform (DTCWT) based modified …

Background Automating cytology-based cervical cancer screening could alleviate the
shortage of skilled pathologists in developing countries. Up until now, computer vision …

Cervical cancer identification through pap-smear images analysis is a challenge for
medicians, especially in distinguishing cells, between the normal and abnormal one. This …

Cervical cancer is one of the fastest growing global health problems and leading cause of
mortality among women of developing countries. Automated Pap smear cell recognition and …

Cervical cancer is one of the most common and deadliest cancers among women. Despite
that, this cancer is entirely treatable if it is detected at a precancerous stage. Pap smear test …

Cervical intraepithelial neoplasia (CIN) and cervical cancer are major health problems faced
by women worldwide. The conventional Papanicolaou (Pap) smear analysis is an effective …

We presented a comparative work of deep learning models for Pap smear classification. The
benchmark parameters used to compare are accuracy, specificity, computation time, and …

Objective: Automated Pap smear cervical screening is one of the most effective imaging
based cancer detection tools used for categorizing cervical cell images as normal and …