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A novel classification with deep convolutional neural networks on pulmonary nodule

Show simple item record MATHEWS, Arun B. PRASAD, Krishna K. 2022-10-18T10:21:51Z 2022-10-18T10:21:51Z 2022
dc.identifier.citation MATHEWS, Arun B., PRASAD, Krishna K. A novel classification with deep convolutional neural networks on pulmonary nodule. In: Journal of Engineering Science. 2022, V. 29, N. 3, pp. 86-92. ISSN 2587-3474, eISSN 2587-3482. en_US
dc.identifier.issn 2587-3474
dc.identifier.issn 2587-3482
dc.description.abstract Medical images are an important part of a patient's health record, and they need data manipulation, processing, and handling by computers. As a result, medical data is a type of bigdata, and its analysis has become complex. Because manual disease diagnosis takes longer and produces less accurate results, it may result in incorrect treatment. Three DCNN architectures have been exploited and evaluated for tumor detection and classification. The sample image for the experimentation is chosen from Lung Image Database Consortium (LIDC) with Image Database Resource Initiative (IDRI) and Kaggle dataset which consists of normal and abnormal image. The experimental results of proposed DCNN classifier achieved best accuracy than the GoogleNet, AlexNet, Artificial neural network and support vector machine. en_US
dc.description.abstract Imaginile medicale sunt o parte importantă a dosarului de sănătate al pacientului și necesită manipularea, procesarea și manipularea datelor de către computere. Drept urmare, datele medicale sunt un tip de bigdata, iar analiza lor a devenit complexă. Deoarece diagnosticarea manuală a bolii durează mult și produce rezultate mai puțin precise, aceasta poate duce la un tratament incorect. Trei arhitecturi DCNN au fost exploatate și evaluate pentru detectarea și clasificarea tumorilor. Imaginea eșantion pentru experimentare este aleasă din Lung Image Database Consortium (LIDC) cu Image Database Resource Initiative (IDRI) și setul de date Kaggle care constă dintr-o imagine normală și anormală. Rezultatele experimentale ale clasificatorului DCNN propus au obținut mai bună acuratețe decât GoogleNet, AlexNet, rețeaua neuronală artificială și mașina de suport vector. en_US
dc.language.iso en en_US
dc.publisher Technical University of Moldova en_US
dc.relation.ispartofseries Journal of Engineering Science;2022, V. 29, N. 3
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri *
dc.subject medical images en_US
dc.subject lung cancer en_US
dc.subject imagini medicale en_US
dc.subject cancer pulmonar en_US
dc.subject GoogleNet
dc.subject AlexNet
dc.title A novel classification with deep convolutional neural networks on pulmonary nodule en_US
dc.title.alternative O nouă clasificare cu rețele neuronale convoluționale profunde pe nodul pulmonar en_US
dc.type Article en_US

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