Mr Md Mamunur Rahaman
Casual Academic

Mr Md Mamunur Rahaman

Engineering
Computer Science and Engineering

Md Mamunur Rahaman is a PhD Scholar in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney. His research focuses on developing innovative image processing methods, algorithms, and software systems for computer-aided diagnostics. He is interested in studying medical imaging and microscopic images and developing an advanced computational method to convert the image data to knowledge or some form of medical intervention.

He received a BSc Degree in Electrical & Electronics Engineering from BRAC University, Dhaka, Bangladesh, in 2017 and the M.Eng. Degree in Biomedical Engineering from Northeastern University, China, in 2021. He worked as a research assistant (RA) with the Microscopic Image and Medical Image Analysis Group, College of Medicine and Bioinformatics Engineering, Northeastern University, from 2021 to 2022.

  • Journal articles | 2023
    Kulwa F; Li C; Grzegorzek M; Rahaman MM; Shirahama K; Kosov S, 2023, 'Segmentation of weakly visible environmental microorganism images using pair-wise deep learning features', Biomedical Signal Processing and Control, vol. 79, pp. 104168 - 104168, http://dx.doi.org/10.1016/j.bspc.2022.104168
    Journal articles | 2022
    Chen A; Li C; Zou S; Rahaman MM; Yao Y; Chen H; Yang H; Zhao P; Hu W; Liu W; Grzegorzek M, 2022, 'SVIA dataset: A new dataset of microscopic videos and images for computer-aided sperm analysis', Biocybernetics and Biomedical Engineering, vol. 42, pp. 204 - 214, http://dx.doi.org/10.1016/j.bbe.2021.12.010
    Journal articles | 2022
    Chen H; Li C; Li X; Rahaman MM; Hu W; Li Y; Liu W; Sun C; Sun H; Huang X; Grzegorzek M, 2022, 'IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach', Computers in Biology and Medicine, vol. 143, http://dx.doi.org/10.1016/j.compbiomed.2022.105265
    Journal articles | 2022
    Chen H; Li C; Wang G; Li X; Mamunur Rahaman M; Sun H; Hu W; Li Y; Liu W; Sun C; Ai S; Grzegorzek M, 2022, 'GasHis-Transformer: A multi-scale visual transformer approach for gastric histopathological image detection', Pattern Recognition, vol. 130, http://dx.doi.org/10.1016/j.patcog.2022.108827
    Journal articles | 2022
    Hu W; Li C; Li X; Rahaman MM; Ma J; Zhang Y; Chen H; Liu W; Sun C; Yao Y; Sun H; Grzegorzek M, 2022, 'GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer', Computers in Biology and Medicine, vol. 142, http://dx.doi.org/10.1016/j.compbiomed.2021.105207
    Journal articles | 2022
    Li X; Li C; Rahaman MM; Sun H; Li X; Wu J; Yao Y; Grzegorzek M, 2022, 'A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches', Artificial Intelligence Review, vol. 55, pp. 4809 - 4878, http://dx.doi.org/10.1007/s10462-021-10121-0
    Journal articles | 2022
    Li Y; Li C; Li X; Wang K; Rahaman MM; Sun C; Chen H; Wu X; Zhang H; Wang Q, 2022, 'A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis', Archives of Computational Methods in Engineering, vol. 29, pp. 609 - 639, http://dx.doi.org/10.1007/s11831-021-09591-w
    Journal articles | 2022
    Li Y; Wu X; Li C; Li X; Chen H; Sun C; Rahaman MM; Yao Y; Zhang Y; Jiang T, 2022, 'A hierarchical conditional random field-based attention mechanism approach for gastric histopathology image classification', Applied Intelligence, vol. 52, pp. 9717 - 9738, http://dx.doi.org/10.1007/s10489-021-02886-2
    Journal articles | 2022
    Liu W; Li C; Rahaman MM; Jiang T; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, 'Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From convolutional neural networks to visual transformers', Computers in Biology and Medicine, vol. 141, http://dx.doi.org/10.1016/j.compbiomed.2021.105026
    Journal articles | 2022
    Liu W; Li C; Xu N; Jiang T; Rahaman MM; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, 'CVM-Cervix: A hybrid cervical Pap-smear image classification framework using CNN, visual transformer and multilayer perceptron', PATTERN RECOGNITION, vol. 130, http://dx.doi.org/10.1016/j.patcog.2020.108829
    Journal articles | 2022
    Liu W; Li C; Xu N; Jiang T; Rahaman MM; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, 'CVM-Cervix: A hybrid cervical Pap-smear image classification framework using CNN, visual transformer and multilayer perceptron', Pattern Recognition, vol. 130, http://dx.doi.org/10.1016/j.patcog.2022.108829
    Journal articles | 2022
    Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2022, 'A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements', Archives of Computational Methods in Engineering, http://dx.doi.org/10.1007/s11831-022-09811-x
    Journal articles | 2022
    Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2022, 'A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches', Artificial Intelligence Review, vol. 55, pp. 2875 - 2944, http://dx.doi.org/10.1007/s10462-021-10082-4
    Journal articles | 2022
    Zhang J; Zhao X; Jiang T; Rahaman MM; Yao Y; Lin YH; Zhang J; Pan A; Grzegorzek M; Li C, 2022, 'An Application of Pixel Interval Down-Sampling (PID) for Dense Tiny Microorganism Counting on Environmental Microorganism Images', Applied Sciences (Switzerland), vol. 12, http://dx.doi.org/10.3390/app12147314
    Journal articles | 2022
    Zhao P; Li C; Rahaman MM; Xu H; Ma P; Yang H; Sun H; Jiang T; Xu N; Grzegorzek M, 2022, 'EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification, and Detection Method Evaluation', Frontiers in Microbiology, vol. 13, http://dx.doi.org/10.3389/fmicb.2022.829027
    Journal articles | 2021
    Ai S; Li C; Li X; Jiang T; Grzegorzek M; Sun C; Rahaman MM; Zhang J; Yao Y; Li H, 2021, 'A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development', BioMed Research International, vol. 2021, http://dx.doi.org/10.1155/2021/6671417
    Journal articles | 2021
    Li Z; Li C; Yao Y; Zhang J; Rahaman M; Xu H; Kulwa F; Lu B; Zhu X; Jiang T, 2021, 'EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks', PLoS ONE, vol. 16, http://dx.doi.org/10.1371/journal.pone.0250631
    Journal articles | 2021
    Rahaman MM; Li C; Yao Y; Kulwa F; Wu X; Li X; Wang Q, 2021, 'DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques', Computers in Biology and Medicine, vol. 136, http://dx.doi.org/10.1016/j.compbiomed.2021.104649
    Journal articles | 2020
    Li X; Li C; Kulwa F; Rahaman MM; Zhao W; Wang X; Xue D; Yao Y; Cheng Y; Li J; Qi S; Jiang T, 2020, 'Foldover Features for Dynamic Object Behaviour Description in Microscopic Videos', IEEE Access, vol. 8, pp. 114519 - 114540, http://dx.doi.org/10.1109/ACCESS.2020.3003993
    Journal articles | 2020
    Rahaman MM; Li C; Wu X; Yao Y; Hu Z; Jiang T; Li X; Qi S, 2020, 'A survey for cervical cytopathology image analysis using deep learning', IEEE Access, vol. 8, pp. 61687 - 61710, http://dx.doi.org/10.1109/ACCESS.2020.2983186
    Journal articles | 2020
    Rahaman MM; Li C; Yao Y; Kulwa F; Rahman MA; Wang Q; Qi S; Kong F; Zhu X; Zhao X, 2020, 'Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches', Journal of X-Ray Science and Technology, vol. 28, pp. 821 - 839, http://dx.doi.org/10.3233/XST-200715
    Journal articles | 2020
    Sun C; Li C; Zhang J; Rahaman MM; Ai S; Chen H; Kulwa F; Li Y; Li X; Jiang T, 2020, 'Gastric histopathology image segmentation using a hierarchical conditional random field', Biocybernetics and Biomedical Engineering, vol. 40, pp. 1535 - 1555, http://dx.doi.org/10.1016/j.bbe.2020.09.008
    Journal articles | 2020
    Xu H; Li C; Rahaman MM; Yao Y; Li Z; Zhang J; Kulwa F; Zhao X; Qi S; Teng Y, 2020, 'An enhanced framework of generative adversarial networks (EF-GANs) for environmental microorganism image augmentation with limited rotationinvariant training data', IEEE Access, vol. 8, pp. 187455 - 187469, http://dx.doi.org/10.1109/ACCESS.2020.3031059
    Journal articles | 2020
    Xue D; Zhou X; Li C; Yao Y; Rahaman MM; Zhang J; Chen H; Zhang J; Qi S; Sun H, 2020, 'An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification', IEEE Access, vol. 8, pp. 104603 - 104618, http://dx.doi.org/10.1109/ACCESS.2020.2999816
    Journal articles | 2020
    Zhou X; Li C; Rahaman MM; Yao Y; Ai S; Sun C; Wang Q; Zhang Y; Li M; Li X; Jiang T; Xue D; Qi S; Teng Y, 2020, 'A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks', IEEE Access, vol. 8, pp. 90931 - 90956, http://dx.doi.org/10.1109/ACCESS.2020.2993788
  • Preprints | 2021
    Li C; Li X; Rahaman M; Li X; Sun H; Zhang H; Zhang Y; Li X; Wu J; Yao Y; Grzegorzek M, 2021, A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches, http://arxiv.org/abs/2102.10553v1
    Conference Papers | 2021
    Li Y; Wu X; Li C; Sun C; Li X; Rahaman M; Zhang Y, 2021, 'Intelligent Gastric Histopathology Image Classification Using Hierarchical Conditional Random Field based Attention Mechanism', in ACM International Conference Proceeding Series, pp. 330 - 335, http://dx.doi.org/10.1145/3457682.3457733
    Preprints | 2021
    Li Y; Wu X; Li C; Sun C; Rahaman M; Chen H; Yao Y; Li X; Zhang Y; Jiang T, 2021, A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification, http://arxiv.org/abs/2102.10499v2
    Preprints | 2021
    Li Z; Li C; Yao Y; Zhang J; Rahaman MM; Xu H; Kulwa F; Lu B; Zhu X; Jiang T, 2021, EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks, http://dx.doi.org/10.1371/journal.pone.0250631
    Preprints | 2021
    Rahaman MM; Li C; Yao Y; Kulwa F; Wu X; Li X; Wang Q, 2021, DeepCervix: A Deep Learning-based Framework for the Classification of Cervical Cells Using Hybrid Deep Feature Fusion Techniques, http://dx.doi.org/10.1016/j.compbiomed.2021.104649
    Preprints | 2021
    Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2021, A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approaches, http://arxiv.org/abs/2103.13625v4
    Preprints | 2020
    Li Y; Li C; Li X; Wang K; Rahaman MM; Sun C; Chen H; Wu X; Zhang H; Wang Q, 2020, A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis, http://dx.doi.org/10.1007/s11831-021-09591-w
    Conference Papers | 2019
    Rahaman MM; Chowdhury A; Islam M; Rahman MM, 2019, 'CZTS based thin film solar cell: An investigation into the influence of dark current on cell performance', in 2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018, pp. 87 - 92, http://dx.doi.org/10.1109/ICIEV.2018.8641013