MaxCerVixT: A novel lightweight vision transformer-based Approach for precise cervical cancer detection

I Pacal - Knowledge-Based Systems, 2024 - Elsevier
Early detection is essential for cervical cancer therapy, which is the fourth most frequent
malignancy worldwide. While the Pap smear test is the established approach for identifying …

Deep learning-based approaches for robust classification of cervical cancer

I Pacal, S Kılıcarslan - Neural Computing and Applications, 2023 - Springer
Cervical cancer is the fourth most common cancer worldwide, and early diagnosis is crucial
for successful treatment, as with all types of cancer. The pap-smear test is considered the …

Precision medicine in digital pathology via image analysis and machine learning

PD Caie, N Dimitriou, O Arandjelović - Artificial Intelligence in Pathology, 2025 - Elsevier
In this chapter, we present the concept that digital pathology and artificial intelligence can
add value and speed to a pathologist's diagnosis while striving toward precision medicine …

Colorectal cancer outcome prediction from H&E whole slide images using machine learning and automatically inferred phenotype profiles

X Yue, N Dimitriou, O Arandjelovic - arxiv preprint arxiv:1902.03582, 2019 - arxiv.org
Digital pathology (DP) is a new research area which falls under the broad umbrella of health
informatics. Owing to its potential for major public health impact, in recent years DP has …

Application of artificial intelligence algorithms on modeling of reflection phase characteristics of a nonuniform reflectarray element

P Mahouti - … Modelling: Electronic Networks, Devices and Fields, 2020 - Wiley Online Library
Reflectarray antennas (RAs) have the ability to combine the advantages of both traditional
parabolic reflector and phased array antennas without the need for feed network designs …

Segmentation technique for medical image processing: A survey

R Merjulah, J Chandra - 2017 international conference on …, 2017 - ieeexplore.ieee.org
Segmentation is one of the popular and efficient technique in context to medical image
analysis. The purpose of the segmentation is to clearly extract the Region of Interest from the …

Artificial classification of cervical squamous lesions in ThinPrep cytologic tests using a deep convolutional neural network

L Liu, Y Wang, Q Ma, L Tan, Y Wu… - Oncology …, 2020 - spandidos-publications.com
The diagnosis of squamous cell carcinoma requires the accurate classification of cervical
squamous lesions in the ThinPrep cytologic test (TCT). It primarily relies on a pathologist's …

Comparison of tissue classification performance by deep learning and conventional methods on colorectal histopathological images

Z Karhan, F Akal - 2020 Medical Technologies Congress …, 2020 - ieeexplore.ieee.org
The automatic evaluation is essential for the diagnosis and treatment of the disease of
pathological images. Computer-aided systems are becoming more common day by day in …

[PDF][PDF] Leukemia Cancer Cells Segmentation and Classification using Machine Learning

M Rajamanickam, C Meenakshi - Leukemia, 2024 - iciset.in
Determining the aim of the project is to detect the leukemia at earlier stage with the help of
image processing techniques. Leukemia means blood cancer which is featured by the …

Classification of histopathological images by spatial feature extraction and morphological methods

CE Tezcan, B Kiras, G Bilgin - 2021 Medical Technologies …, 2021 - ieeexplore.ieee.org
The high accuracy of the computerized analysis of histopathological images is very
important in the detection of cancerous cells. Thanks to the images with high accuracy, early …