A Multi-modal Approach to Lung Tumor Detection using Deep Learning
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Lung cancer remains a significant global cause of cancer-related deaths, emphasizing the importance of early detection for improving patient survival rates. This paper introduces an enhanced approach that aims to achieve efficient and precise lung tumor detection and segmentation. The proposed method utilizes a multimodal approach by leveraging both CT and PET scans, enabling improved tumor detection. The methodology incorporates state-of-The-Art deep learning architectures, including ResNet, DenseNet, and Inception-v3, for effective tumor classification. Additionally, both immediate fusion (early fusion) and late fusion techniques are applied to integrate data from multiple modalities. The performance of the classification models is evaluated using metrics such as precision, F1 score, accuracy, and sensitivity. The experimental results demonstrate the effectiveness of the proposed approach in accurately segmenting lung tumors. The findings contribute to the existing knowledge in the field of tumor segmentation and medical image analysis, providing valuable insights into the benefits of multimodal fusion and deep learning techniques for lung cancer diagnosis and treatment planning. © 2023 IEEE.
Açıklama
Central Michigan University (CMU);IEEE
2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023 -- 16 September 2023 through 17 September 2023 -- -- 194014
2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023 -- 16 September 2023 through 17 September 2023 -- -- 194014
Anahtar Kelimeler
Deep Learning, Feature Fusion, Lung Tumor, Multimodal Feature Extraction, Tumor Detection And Segmentation
Kaynak
2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023 - Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
