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 …

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

Purpose Liver cancer is one of the most common malignant tumors in the world, ranking fifth
in malignant tumors. The degree of differentiation can reflect the degree of malignancy. The …

Cervical cancer is the one of the most common cancers in women worldwide, affecting
around 570,000 new patients each year. Although there have been great improvements …

Current automation‐assisted technologies for screening cervical cancer mainly rely on
automated liquid‐based cytology slides with proprietary stain. This is not a cost‐efficient …

Routine Pap smears can facilitate early detection of cervical cancer and improve patient
outcomes. The objective of this work is to develop an automated, clinically viable deep …

This paper introduces a modified version of the Hybrid Multilayer Perceptron (HMLP)
network to improve the performance of the conventional HMLP network. We adopted the …

Accurate classification of Pap smear images becomes the challenging task in medical image
processing. This can be improved in two ways. One way is by selecting suitable well defined …

Advent of medical image digitalization leads to image processing and computer‐aided
diagnosis systems in numerous clinical applications. These technologies could be used to …

Abstract In this paper, Levenberg–Marquardt feedforward MLP neural network (LMFFNN)
was proposed to classify cervical cell images obtained from 100 patients including healthy …