Author(s): Islam M; Zunair H; Mohammed N;

Crafting effective deep learning models for medical image analysis is a complex task, particularly in cases where the medical image dataset lacks significant inter-class variation. This challenge is further aggravated when employing such datasets to generate synthetic images using generative adversarial networks (GANs), as the output of GANs heavily relie ...

Article GUID: 38492455

Author(s): Depto DS; Rizvee MM; Rahman A; Zunair H; Rahman MS; Mahdy MRC;

Uncontrolled proliferation of B-lymphoblast cells is a common characterization of Acute Lymphoblastic Leukemia (ALL). B-lymphoblasts are found in large numbers in peripheral blood in malignant cases. Early detection of the cell in bone marrow is essential as the disease progresses rapidly if left untreated. However, automated classification of the cell is ...

Article GUID: 36516574

Author(s): Khan MS; Alam KN; Dhruba AR; Zunair H; Mohammed N;

Melanoma is regarded as the most threatening among all skin cancers. There is a pressing need to build systems which can aid in the early detection of melanoma and enable timely treatment to patients. Recent methods are geared towards machine learning based systems where the task is posed as image recognition, tag dermoscopic images of skin lesions as mel ...

Article GUID: 35594685

Author(s): Zunair H; Ben Hamza A;

The U-Net architecture, built upon the fully convolutional network, has proven to be effective in biomedical image segmentation. However, U-Net applies skip connections to merge semantically different low- and high-level convolutional features, resulting in not only blurred feature maps, but also over- and under-segmented target regions. To address these ...

Article GUID: 34348214

Author(s): Rahman A, Zunair H, Reme TR, Rahman MS, Mahdy MRC

Malaria, one of the leading causes of death in underdeveloped countries, is primarily diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task owing to the fine-grained variability in the appearance of some uninfected and infected class. In this paper, we transform a malaria parasite object detection dataset into a classificat ...

Article GUID: 33465520

Author(s): Zunair H, Ben Hamza A

Phys Med Biol. 2020 Apr 06;: Authors: Zunair H, Ben Hamza A

Article GUID: 32252036