Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis

Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis

Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Develop a computer-aided d...

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Bibliographic Details
Published in:Journal of personalized medicine Vol. 13; no. 3; p. 388
Main Authors: Althubaity, DaifAllah D, Alotaibi, Faisal Fahad, Osman, Abdalla Mohamed Ahmed, Al-Khadher, Mugahed Ali, Abdalla, Yahya Hussein Ahmed, Alwesabi, Sadeq Abdo, Abdulrahman, Elsadig Eltaher Hamed, Alhemairy, Maram Abdulkhalek
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 23-02-2023
MDPI
Subjects:
Automation
Biopsy
Cancer
Datasets
Development and progression
Diagnosis
Disease
Histopathology
Lung cancer
Medical imaging
Medical prognosis
Precision medicine
Software
Tumors
Saudi Arabia
lung cancer
histopathological images
TMA
Tumor
automatic identification
CAD
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Summary:Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer.
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ISSN:2075-4426
2075-4426
DOI:10.3390/jpm13030388