Review article
https://doi.org/10.31534/engmod.2025.1.ri.05m
Early Detection and Classification of Cancer Histology Images Using Artificial Intelligence Techniques: A Review
Soufiane El Aamrani
orcid.org/0009-0005-7106-6781
; Data4Earth laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, MOROCCO
Anass Abdelhamid El Alami
; Data4Earth laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, MOROCCO
Omar Fikri
; Data4Earth laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, MOROCCO
Abdelali Elmoufidi
orcid.org/0000-0002-8574-9584
; L.A.R.P.E.G laboratory, National School of Commerce and Management Casablanca, Hassan II University, Casablanca, MOROCCO
*
Mohammed Erritali
orcid.org/0000-0002-1672-8085
; Data4Earth laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, MOROCCO
* Corresponding author.
Abstract
Cancer is one of the most serious diseases that humans face nowadays, and, until now, no permanent remedy has been developed for it, especially in the case of advanced stages. Cancer is characterised by uncontrolled multiplication and abnormal growth of cells until tumour formation and organ destruction. Early detection and diagnosis are imperative to reduce the number of mortalities, which has progressively declined in recent years thanks to more advanced computer-aided diagnosis systems (CADS). Artificial intelligence and machine learning have been successfully applied to detect and treat various dangerous diseases. It is more accurate to use histopathological imaging to detect cancers such as breast, lung, and brain cancer in the early stage based on more important features. In this paper, we review previous work on various types of cancer using microscopic and histopathological imaging as datasets on different deep learning and artificial intelligence models for classifying abnormalities. The aim is to provide a comprehensive view of the existing techniques and datasets for detecting and classifying histopathological images.
Keywords
cancer detection; histopathological imaging; artificial intelligence; medical image analysis
Hrčak ID:
329015
URI
Publication date:
20.3.2025.
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