Browsing Articles by Author "Rafid, A.K.M. Rakibul Haque"

Now showing items 1-3 of 3

Automated Detection of Broncho-Arterial Pairs Using CT Scans Employing Different Approaches To Classify Lung Diseases

Azam, Sami; Rafid, A.K.M. Rakibul Haque; Montaha, Sidratul; Karim, Asif; Jonkman, Mirjam; Boer, Friso De (MDPI Publications, 2023-01-05)

Current research indicates that for the identification of lung disorders, comprising pneumonia and COVID-19, structural distortions of bronchi and arteries (BA) should be taken into account. CT scans are an effective ...
An Effective Approach To Address Processing Time and Computational Complexity Employing Modified CCT for Lung Disease Classification

Khan, Inam Ullah; Azam, Sami; Montaha, Sidratul; Mahmud, Abdullah Al; Rafid, A.K.M. Rakibul Haque; Hasan, Md. Zahid; Jonkman, Mirjam (Scopus, 22-11-22)

Early identification and adequate treatment can help prevent lung disorders from becoming chronic, severe, and life-threatening. X-ray images are commonly used and an automated and effective method involving deep learning ...
Using feature maps to unpack the CNN ‘Black box’ theory with two medical datasets of different modality

Azam, Sami; Montaha, Sidratul; Fahim, Kayes Uddin; Rafid, A.K.M. Rakibul Haque; Mukta, Md. Saddam Hossain; Jonkman, Mirjam (Daffodil International University, 2023-05)

Convolutional neural networks (CNNs) have been established for a comprehensive range of computer vision problems across several benchmarks. Visualization and analysis of feature maps generated by convolutional layers can ...

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