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Browsing Articles by Author "Montaha, Sidratul"

Browsing Articles by Author "Montaha, Sidratul"

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  • Automated Breast Tumor Ultrasound Image Segmentation With Hybrid UNet and Classification Using Fine-Tuned CNN Model 
    Hossain, Shahed; Azam, Sami; Montaha, Sidratul; Karim, Asif; Chowa, Sadia Sultana; Mondol, Chaity; Hasan, Md Zahid; Jonkman, Mirjam (Elsevier, 2023-10-20)
    Introduction Breast cancer stands as the second most deadly form of cancer among women worldwide. Early diagnosis and treatment can significantly mitigate mortality rates. Purpose The study aims to classify breast ...
  • 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 ...
  • Brain Tumor Segmentation from 3D MRI Scans Using U-Net 
    Montaha, Sidratul; Azam, Sami (Springer, 2023-05-11)
    Segmentation of brain tumor from 3D images is one of the most important and difficult tasks in the field of medical image processing as a manual human-assisted categorization can result in incorrect prediction and diagnosis. ...
  • Breastnet18 
    Montaha, Sidratul; Azam, Sami; Muhammad Rakibul Haque Rafid, Abul Kalam; Ghosh, Pronab; Hasan, Md. Zahid; Jonkman, Mirjam; De Boer, Friso (Biology, 2021-11-13)
    Background: Identification and treatment of breast cancer at an early stage can reduce mortality. Currently, mammography is the most widely used effective imaging technique in breast cancer detection. However, an erroneous ...
  • Deep Learning-Based Analysis of COVID-19 X-Ray Images: Incorporating Clinical Significance and Assessing Misinterpretation 
    Bhuiyan, Md. Rahad Islam; Azam, Sami; Montaha, Sidratul; Jim, Risul Islam; Karim, Asif; Khan, Inam Ullah; Brady, Mark; Hasan, Md. Zahid; Boer, Friso De; Mukta, Md. Saddam Hossain (SAGE Publications, 2023-11-06)
    COVID-19, pneumonia, and tuberculosis have had a significant effect on recent global health. Since 2019, COVID-19 has been a major factor underlying the increase in respiratory-related terminal illness. Early-stage ...
  • 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 ...
  • Ergonomic Risk Prediction for Awkward Postures From 3D Keypoints Using Deep Learning 
    Hossain, MD. Shakhaout; Azam, Sami; Karim, Asif; Montaha, Sidratul; Quadir, Ryana; Boer, Friso De; Altaf-Ul-Amin, MD. (IEEE, 2023-10-20)
    Work-related musculoskeletal ailments are injuries or disorders of the joints, muscles, nerves, or tendons caused by repetitive tasks and jobs that require uncomfortable postures. REBA (Rapid Entire Body Assessment) is a ...
  • Graph Neural Network-Based Breast Cancer Diagnosis Using Ultrasound Images With Optimized Graph Construction Integrating the Medically Significant Features 
    Chowa, Sadia Sultana; Azam, Sami; Montaha, Sidratul; Payel, Israt Jahan; Bhuiyan, Md Rahad Islam; Hasan, Md. Zahid; Jonkman, Mirjam (MDPI Publications, 2023-11-20)
    Purpose An automated computerized approach can aid radiologists in the early diagnosis of breast cancer. In this study, a novel method is proposed for classifying breast tumors into benign and malignant, based on the ...
  • MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data 
    Hasib, Khan Md.; Azam, Sami; Karim, Asif; Marouf, Ahmed Al; Shamrat, F M Javed Mehedi; Montaha, Sidratul; Yeo, Kheng Cher; Jonkman, Mirjam (IEEE, 2023-08-29)
    "Searching, retrieving, and arranging text in ever-larger document collections necessitate more efficient information processing algorithms. Document categorization is a crucial component of various information ...
  • MNet-10 
    Montaha, Sidratul; Azam, Sami; Rafid, A. K. M. Rakibul Haque; Hasan, Md. Zahid; Karim, Asif; Hasib, Khan Md.; Patel, Shobhit K.; Jonkman, Mirjam; Mannan, Zubaer Ibna (Daffodil International University, 2022-08-22)
    Interpretation of medical images with a computer-aided diagnosis (CAD) system is arduous because of the complex structure of cancerous lesions in different imaging modalities, high degree of resemblance between inter-classes, ...
  • A Novel Data and Model Centric Artificial Intelligence Based Approach in Developing High-Performance Named Entity Recognition for Bengali Language 
    Lima, Khadija Akter; Hasib, Khan Md; Azam, Sami; Karim, Asif; Montaha, Sidratul; Noori, Sheak Rashed Haider; Jonkman, Mirjam (PLOS ONE, 2023-09-22)
    Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of domain specific applications in Natural Language Processing (NLP). According to the type of application, the goal of NER ...
  • A Robust Framework Combining Image Processing and Deep Learning Hybrid Model to Classify Cardiovascular Diseases Using a Limited Number of Paper-Based Complex ECG Images 
    Fatema, Kaniz; Montaha, Sidratul; Rony, Md. Awlad Hossen; Azam, Sami; Hasan, Md. Zahid; Jonkman, Mirjam (Scopus, 22-11-07)
    Heart disease can be life-threatening if not detected and treated at an early stage. The electrocardiogram (ECG) plays a vital role in classifying cardiovascular diseases, and often physicians and medical researchers examine ...
  • Time Distributed -CNN-LSTM 
    Montaha, Sidratul; Azam, Sami; Rafid, A. K. M. Rakibul Haque; Hasan, MD. Zahid; Karim, Asif; Islam, Ashraful (Daffodil International University, 2022-06-10)
    Identification of brain tumors at an early stage is crucial in cancer diagnosis, as a timely diagnosis can increase the chances of survival. Considering the challenges of tumor biopsies, three dimensional (3D) Magnetic ...
  • 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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