By Mr Md Mamunur Rahaman

Preprints

Rahaman MM; Millar EKA; Meijering E, 2023, Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning, http://dx.doi.org/10.21203/rs.3.rs-2983276/v1

Rahaman MM; Millar EKA; Meijering E, 2023, Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learning, http://dx.doi.org/10.1038/s41598-023-40219-0

Chen A; Zhang J; Rahaman MM; Sun H; D. M; Zeng T; Grzegorzek M; Fan F-L; Li C, 2023, ACTIVE: A Deep Model for Sperm and Impurity Detection in Microscopic Videos, http://dx.doi.org/10.48550/arxiv.2301.06002

Kulwa F; Li C; Grzegorzek M; Rahaman MM; Shirahama K; Kosov S, 2022, Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features, http://dx.doi.org/10.48550/arxiv.2208.14957

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, http://dx.doi.org/10.48550/arxiv.2206.03368

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, http://dx.doi.org/10.48550/arxiv.2206.00971

Zhang J; Zhao X; Jiang T; Rahaman MM; Yao Y; Lin Y-H; 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, http://dx.doi.org/10.48550/arxiv.2204.01341

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, http://dx.doi.org/10.48550/arxiv.2202.09020

Hu W; Li C; Li X; Rahaman MM; Zhang Y; Chen H; Liu W; Yao Y; Sun H; Xu N; Huang X; Grzegorze M, 2022, EBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation, http://dx.doi.org/10.48550/arxiv.2202.08552

Li X; Chen H; Li C; Rahaman MM; Li X; Wu J; Li X; Sun H; Grzegorzek M, 2022, What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review, http://dx.doi.org/10.48550/arxiv.2201.08550

Zhao P; Li C; Rahaman MM; Xu H; Ma P; Yang H; Sun H; Jiang T; Xu N; Grzegorzek M, 2021, EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation, http://dx.doi.org/10.48550/arxiv.2112.07111

Zhao P; Li C; Rahaman MM; Xu H; Yang H; Sun H; Jiang T; Grzegorzek M, 2021, A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers, http://dx.doi.org/10.48550/arxiv.2107.07699

Hu W; Li C; Li X; Rahaman MM; Ma J; Zhang Y; Chen H; Liu W; Sun C; Yao Y; Sun H; Grzegorzek M, 2021, GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer, http://dx.doi.org/10.48550/arxiv.2106.02473

Ma P; Li C; Rahaman MM; Yao Y; Zhang J; Zou S; Zhao X; Grzegorzek M, 2021, A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches, http://dx.doi.org/10.48550/arxiv.2105.03148

Chen H; Li C; Wang G; Li X; Rahaman M; Sun H; Hu W; Li Y; Liu W; Sun C; Ai S; Grzegorzek M, 2021, GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection, http://dx.doi.org/10.48550/arxiv.2104.14528

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

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

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

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

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

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

Zhou X; Li C; Rahaman MM; Yao Y; Ai S; Sun C; Li X; Wang Q; Jiang T, 2020, A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks, http://dx.doi.org/10.48550/arxiv.2003.12255

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