Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Md. Zahid Hasan et al.
Identification of brain tumors and accurate grading at an early stage are crucial in cancer diagnosis, as a timely diagnosis can increase the chances of survival. Considering the challenges and risks of tumor biopsies, noninvasive imaging procedures such as Magnetic Resonance Imaging (MRI) are exten...
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Pronab Ghosh et al.
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 mammogram based interpretation may result in false diagnosis rate, as disting...
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Md. Zahid Hasan et al.
Abstract A fully automated system based on three-dimensional (3D) magnetic resonance imaging (MRI) scans for brain tumor segmentation could be a diagnostic aid to clinical specialists, as manual segmentation is challenging, arduous, tedious and error prone. Employing 3D convolutions requires large c...
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Md. Zahid Hasan et al.
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, presence of dissimilar characteristics in intra-classes, scarcity of medic...
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Sayma Islam et al.
The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class resemblance between malignant and benign lesions, and the presence of various artifacts including hairs make automated melanoma recognition in dermoscopy images quite challenging. To date, various co...
A. K. M. Rakibul Haque Rafid, Sami Azam, Sidratul Montaha, Asif Karim et al.
Background: Breast cancer, behind skin cancer, is the second most frequent malignancy among women, initiated by an unregulated cell division in breast tissues. Although early mammogram screening and treatment result in decreased mortality, differentiating cancer cells from surrounding tissues are of...
Md. Zahid Hasan, Sidratul Montaha, Inam Ullah Khan, Md. Mehedi Hassan et al.
A novel automated multi-classification approach is proposed for the anticipation of lung abnormalities using chest X-ray and CT images. The study leverages a publicly accessible dataset with an insufficient and unbalanced number of images, addressing this issue by employing the data augmentation app...
Sami Azam, A. K. M. Rakibul Haque Rafid, Sidratul Montaha, Asif Karim et al.
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 modality to detect lung anomalies. However, anomalies in bronchi and arteries can b...
Sami Azam, Sidratul Montaha, Kayes Uddin Fahim, A. K. M. Rakibul Haque Rafid et al.
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 be an effective approach to explore the hidden and complex characteristic of a ...
Inam Ullah Khan, Sami Azam, Sidratul Montaha, Abdullah Al Mahmud et al.
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 techniques can potentially contribute to quick and accurate diagnosis of lung ...
Sami Azam, Sidratul Montaha, Mohaimenul Azam Khan Raiaan, A. K. M. Rakibul Haque Rafid et al.
An automated computer-aided approach might aid radiologists in diagnosing breast cancer at a primary stage. This study proposes a novel decision support system to classify breast tumors into benign and malignant based on clinically important features, using ultrasound images. Nine handcrafted featur...