15 Publications by "Y. M. Kassim"


#352: M. M. H. Shuvo, Y. M. Kassim, F. Bunyak, O. V. Glinskii, L. Xie, V. V. Glinsky, V. H. Huxley, M. M. Thakkar, and K. Palaniappan

Multi-focus Image Fusion for Confocal Microscopy Using U-Net Regression Map

International Conference on Pattern Recognition (ICPR), pgs. 4317-4323, 2021

Bibtex, PlainText, DOI, Google Scholar
#350: D. K. Ufuktepe, F. Yang, Y. M. Kassim, H. Yu, R. J. Maude, K. Palaniappan, and S. Jaeger

Deep Learning-Based Cell Detection and Extraction in Thin Blood Smears for Malaria Diagnosis

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1--6, 2021

malaria diagnosis, plasmodium falciparum, plas-modium vivax, microscopy, thin blood smear, machine learning, image analysis

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#345: E. Asante, D. Hummel, S. Gurung, Y. Kassim, N. Al-Shakarji, K. Palaniappan, V. Sittaramane, and A. Chandrasekhar

Defective neuronal positioning correlates with aberrant motor circuit function in zebrafish

Frontiers in Neural Circuits, Volume 15, 2021

jaw movement, food intake, behavior, neuronal migration, axon guidance, zebrafish, neural circuits, facial branchiomotor neuron, fusion, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#335: Y. M. Kassim, K. Palaniappan, F. Yang, M. Poostchi, N. Palaniappan, R. J. Maude, S. Antani, and S. Jaeger

Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears

2020

Bibtex, PlainText, Software, URL, Google Scholar
#306: Y. M. Kassim, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, G. Guidoboni, and K. Palaniappan

Deep U-Net Regression and Hand-Crafted Feature Fusion for Accurate Blood Vessel Segmentation

2019 IEEE International Conference on Image Processing (ICIP), pgs. 1445-1449, 2019

semantic vessel segmentation, deep learning, histogram equalization, random forests, u-net

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#279: Y. M. Kassim, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, and K. Palaniappan

Patch-Based Semantic Segmentation for Detecting Arterioles and Venules in Epifluorescence Imagery

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-5, 2018

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#273: Y. M. Kassim, R. J. Maude, and K. Palaniappan

Sensitivity of Cross-Trained Deep CNNs for Retinal Vessel Extraction

40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pgs. 2736-2739, 2018

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#293: Y. M. Kassim, N. Al-Shakarji, E. Asante, A. Chandrasekhar, and K. Palaniappan

Dissecting branchiomotor neuron circuits in zebrafish - Toward high-throughput automated analysis of jaw movements

IEEE International Symposium on Biomedical Imaging (ISBI), pgs. 943-947, 2018

zebrafish, branchiomotor circuit, behavior, video microscopy, optical flow, background subtraction, motion map

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#259: Y. M. Kassim and K. Palaniappan

Extracting Retinal Vascular Networks Using Deep Learning Architecture

IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017

deep learning, vessel segmentation, fundoscopy images, patches, convolution neural network

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#257: Y. M. Kassim, V. B. S. Prasath, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, and K. Palaniappan

Microvasculature segmentation of arterioles using deep CNN

IEEE International Conference on Image Processing (ICIP), 2017

deep learning, segmentation, vasculature, biomedical

Abstract, Bibtex, PlainText, URL, Google Scholar
#244: N. Al-Shakarji, Y. Kassim, and K. Palaniappan.

Unsupervised learning method for plant and leaf segmentation

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-4, 2017

plant segmentation, leaf segmentation, watershed, markers, leaves counting

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#235: V. B. S. Prasath, Y. M. Kassim, Z. A. Oraibi, J.-B. Guiriec, A. Hafiane, G. Seetharaman, and K. Palaniappan

HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests

Proc. IEEE International Conference on Pattern Recognition (ICPR), 2016

hep-2 cell classification, cell segmentation, texture features, motif patterns, random forests, segmentation, biomedical

Abstract, Bibtex, PlainText, URL, Google Scholar
#240: Y. M. Kassim, V. B. S. Prasath, O. Glinskii, V. Glinsky, V. Huxley, and K. Palaniappan

Confocal vessel structure segmentation with optimized feature bank and random forests

Proc. IEEE Applied Imagery Pattern Recognition (AIPR), 2016

random forest, segmentation, vasculature, confocal, biomedical

Abstract, Bibtex, PlainText, Google Scholar
#229: S. Meena, V. B. S. Prasath, Y. M. Kassim, R. J. Maude, O. Glinskii, V. Glinsky, V. Huxley, and K. Palaniappan

Multiquadric spline-based interactive segmentation of vascular networks

38th IEEE Engineering in Medicine and Biology Society Conf. (EMBC), pgs. 5913-5916, 2016

interactive, segmentation, vasculature, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#225: Y. M. Kassim, V. B. S. Prasath, R. Pelapur, O. Glinskii, R. J. Maude, V. Glinsky, V. Huxley, and K. Palaniappan

Random forests for dura mater microvasculature segmentation using epifluorescence images

38th IEEE Engineering in Medicine and Biology Society Conf. (EMBC), pgs. 2901-2904, 2016

random forest, segmentation, vasculature, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar