Using Convoluted Neural Networks in Diagnosing Lung Cancer on Computed Tomography Scans.

We proved that a CNN model can easily be implemented on regular hardware to successfully classify malignant and benign lung lesions on CT images. Future CNN implementations can greatly improve the imaging diagnosis of lung lesions; however, the physicians should always decide the medical management.

Authors

Mădălin Mămuleanu (ORCID: https://orcid.org/0000-0003-1524-2494)
Ilona Mihaela Liliac (ORCID: https://orcid.org/0000-0002-4403-7361)
Costin Teodor Streba (ORCID: https://orcid.org/0000-0001-9590-3197)
Mihai Olteanu (ORCID: https://orcid.org/0000-0002-3338-8107)
Ștefan-Vlad Voinea
Ovidiu Lucian Cîmpeanu

Institutions

University of Medicine and Pharmacy of Craiova (RO)
University of Craiova (RO)

Publication Details

Journal: PubMed
Published: 2025-01-01
DOI: https://doi.org/10.12865/chsj.51.01.09
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 0.00

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article

Using Convoluted Neural Networks in Diagnosing Lung Cancer on Computed Tomography Scans.

Mădălin Mămuleanu, Ilona Mihaela Liliac, Costin Teodor Streba, Mihai Olteanu et al.

Jan 1, 2025

PubMed

Radiomics and Machine Learning in Medical Imaging

article

Using Convoluted Neural Networks in Diagnosing Lung Cancer on Computed Tomography Scans.

Mădălin Mămuleanu, Ilona Mihaela Liliac, Costin Teodor Streba, Mihai Olteanu, Ștefan-Vlad Voinea, Ovidiu Lucian Cîmpeanu

January 1, 2025article en

Abstract

We proved that a CNN model can easily be implemented on regular hardware to successfully classify malignant and benign lung lesions on CT images. Future CNN implementations can greatly improve the imaging diagnosis of lung lesions; however, the physicians should always decide the medical management.

PubMedVol. 51(1)

University of Medicine and Pharmacy of Craiova (RO), University of Craiova (RO)

Openalex Percentile: Top 74%

Radiomics and Machine Learning in Medical Imaging

DOI Open Access PDF OpenAlex

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