Zobrazeno 1 - 10
of 181
pro vyhledávání: '"lung nodule classification"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 7, Pp 1705-1724 (2024)
In recent years, deep learning has been widely applied to various classification tasks due to its capability in automatically extracting features and superior classification performance. Research on the classification of lung nodules has gradually sh
Externí odkaz:
https://doaj.org/article/73a9af2f7461493a8b9058dbef9bd05d
Autor:
Tiequn Tang, Rongfu Zhang
Publikováno v:
Journal of Imaging, Vol 10, Iss 9, p 234 (2024)
In the computer-aided diagnosis of lung cancer, the automatic segmentation of pulmonary nodules and the classification of benign and malignant tumors are two fundamental tasks. However, deep learning models often overlook the potential benefits of ta
Externí odkaz:
https://doaj.org/article/3c5e32cc4fce4bdb87e383c554330dfd
Publikováno v:
Frontiers in Medical Technology, Vol 6 (2024)
IntroductionA Computer-Assisted Detection (CAD) System for classification into malignant-benign classes using CT images is proposed.MethodsTwo methods that use the fractal dimension (FD) as a measure of the lung nodule contour irregularities (Box cou
Externí odkaz:
https://doaj.org/article/c83db8949cfd41c19a57b561438b1a92
Publikováno v:
BMC Pulmonary Medicine, Vol 23, Iss 1, Pp 1-12 (2023)
Abstract The accurate recognition of malignant lung nodules on CT images is critical in lung cancer screening, which can offer patients the best chance of cure and significant reductions in mortality from lung cancer. Convolutional Neural Network (CN
Externí odkaz:
https://doaj.org/article/74586954b4224cbca052e52b13353f88
Publikováno v:
Advanced Ultrasound in Diagnosis and Therapy, Vol 7, Iss 3, Pp 272-278 (2023)
Objective: Computed tomography (CT) imaging of the chest is an effective diagnostic tool assisting physicians in making a diagnosis. This study aimed to propose a new convolutional neural network for classifying the lung nodules of the patient throug
Externí odkaz:
https://doaj.org/article/1754c913d17c4406bc089046626bf12b
Attention-guided deep neural network with a multichannel architecture for lung nodule classification
Publikováno v:
Heliyon, Vol 10, Iss 1, Pp e23508- (2024)
Detecting and accurately identifying malignant lung nodules in chest CT scans in a timely manner is crucial for effective lung cancer treatment. This study introduces a deep learning model featuring a multi-channel attention mechanism, specifically d
Externí odkaz:
https://doaj.org/article/2dc0d48da1624bc281281ab2259c7038
Publikováno v:
Diagnostics, Vol 13, Iss 24, p 3690 (2023)
Lung cancer (LC) stands as the foremost cause of cancer-related fatality rates worldwide. Early diagnosis significantly enhances patient survival rate. Nowadays, low-dose computed tomography (LDCT) is widely employed on the chest as a tool for large-
Externí odkaz:
https://doaj.org/article/0a066f5ce2324871abfa38f7861f1bd9
Akademický článek
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Publikováno v:
Journal of Intelligent Systems, Vol 31, Iss 1, Pp 944-964 (2022)
Nowadays, lung cancer is one of the most dangerous diseases that require early diagnosis. Artificial intelligence has played an essential role in the medical field in general and in analyzing medical images and diagnosing diseases in particular, as i
Externí odkaz:
https://doaj.org/article/aed561cdc7bd44d28695a14a9cbbd47e
Publikováno v:
Bioengineering, Vol 10, Iss 11, p 1245 (2023)
Early detection is crucial for the survival and recovery of lung cancer patients. Computer-aided diagnosis system can assist in the early diagnosis of lung cancer by providing decision support. While deep learning methods are increasingly being appli
Externí odkaz:
https://doaj.org/article/624a1a3818c54516ae6d038315fddce3