Dr. Jin Tae Kwak Profile

Dr. Jin Tae Kwak

Associate Professor at Korea Univ

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Publications (14)

Proceedings Article | 3 April 2024 Poster + Paper

Patch stitching data augmentation for cancer classification in pathology images

Jiamu Wang, Chang-Su Kim, Jin Tae Kwak

Proceedings Volume 12933, 129331B (2024) https://doi.org/10.1117/12.3006330

KEYWORDS: Pathology, Image classification, Cancer, Colorectal cancer, Scanners, Performance modeling, Image acquisition, Education and training, Deep convolutional neural networks, Data modeling

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Proceedings Article | 3 April 2024 Presentation + Paper

Efficient semantic segmentation for computational pathology

Doanh Bui, Changsu Kim, Jin Tae Kwak

Proceedings Volume 12933, 129330M (2024) https://doi.org/10.1117/12.3006118

KEYWORDS: Image segmentation, Pathology, Histopathology, Image resolution, Tissues

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Proceedings Article | 7 April 2023 Presentation + Paper

Quintet margin loss for an improved knowledge distillation in histopathology image analysis

Trinh T. Vuong, Jin Tae Kwak

Proceedings Volume 12471, 124710J (2023) https://doi.org/10.1117/12.2654275

KEYWORDS: Education and training, Histopathology, Machine learning, Image analysis, Data modeling, Pathology, Convolution, Adversarial training, Tissues, Prostate

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Proceedings Article | 4 April 2022 Presentation + Paper

A hybrid computational pathology method for the detection of perineural invasion junctions

Chang Hee Han, Jin Tae Kwak

Proceedings Volume 12039, 120390X (2022) https://doi.org/10.1117/12.2610756

KEYWORDS: Tumors, Nerve, Tissues, Image segmentation, Pathology, Cancer, Visualization, Prostate, Colorectal cancer, Colon

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Distance ordinal regression loss for an improved nuclei segmentation

Tan Nhu Nhat Doan, Chang Hee Han, Jin Tae Kwak

Proceedings Volume 11603, 1160315 (2021) https://doi.org/10.1117/12.2581016

KEYWORDS: Image segmentation, Tissues, Pathology, Data modeling, Convolutional neural networks

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

3-D multitask deep neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion

Hoang Long Le, Yejin Jeon, Hong Gee Roh, Hyun Jeong Kim, Jin Tae Kwak

Proceedings Volume 11597, 1159721 (2021) https://doi.org/10.1117/12.2581011

KEYWORDS: Artificial intelligence, Magnetism, Magnetic resonance imaging, 3D image processing, Neural networks, Ischemic stroke, Convolutional neural networks, Capillaries

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Proceedings Article | 18 March 2019 Presentation + Paper

Scale embedding shared neural networks for multiscale histological analysis of prostate cancer

Quy Dinh Duong, Dang Quoc Vu, Daigeun Lee, Stephen Hewitt, Kyungeun Kim, Jin Tae Kwak

Proceedings Volume 10956, 1095606 (2019) https://doi.org/10.1117/12.2512807

KEYWORDS: Tissues, Cancer, Pathology, Neural networks, Convolution, Analytical research, Prostate cancer, Convolutional neural networks, Image analysis

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SPIE Journal Paper | 1 December 2017 Open Access

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

Jin Gwan Ha, Hyeonjoon Moon, Jin Tae Kwak, Syed Ibrahim Hassan, Minh Dang, O New Lee, Han Yong Park

JARS, Vol. 11, Issue 04, 042621, (December 2017) https://doi.org/10.1117/12.10.1117/1.JRS.11.042621

KEYWORDS: Unmanned aerial vehicles, Convolutional neural networks, Image segmentation, RGB color model, Machine learning, Computing systems, Agriculture, Feature extraction, Image processing, Remote sensing

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SPIE Journal Paper | 12 June 2017

Detection of prostate cancer in multiparametric MRI using random forest with instance weighting

Nathan Lay, Yohannes Tsehay, Matthew Greer, Baris Turkbey, Jin Tae Kwak, Peter Choyke, Peter Pinto, Bradford Wood, Ronald Summers

JMI, Vol. 4, Issue 02, 024506, (June 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.2.024506

KEYWORDS: Prostate cancer, Image filtering, Magnetic resonance imaging, Prostate, Computer aided diagnosis and therapy, Feature extraction, Computer aided design, Sensors, Visibility

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Proceedings Article | 3 March 2017 Presentation + Paper

Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images

Yohannes Tsehay, Nathan Lay, Holger Roth, Xiaosong Wang, Jin Tae Kwak, Baris Turkbey, Peter Pinto, Brad Wood, Ronald Summers

Proceedings Volume 10134, 1013405 (2017) https://doi.org/10.1117/12.2254423

KEYWORDS: Tumors, Solid modeling, Biopsy, Cancer, Prostate, Neural networks, Computer aided diagnosis and therapy, Edge detection, Principal component analysis, Computer aided design, Prostate cancer, Magnetic resonance imaging, CAD systems, Evolutionary algorithms

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Proceedings Article | 1 March 2017 Paper

Lumen-based detection of prostate cancer via convolutional neural networks

Jin Tae Kwak, Stephen Hewitt

Proceedings Volume 10140, 1014008 (2017) https://doi.org/10.1117/12.2253513

KEYWORDS: Convolutional neural networks, Image processing, Binary data, Image segmentation, Prostate cancer, Tissues, Neural networks, Cancer, Pathology, Prostate, Cognitive informatics, Image classification, Computer aided diagnosis and therapy, Neurons

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Proceedings Article | 23 March 2016 Paper

High-definition Fourier transform infrared spectroscopic imaging of prostate tissue

Tomasz Wrobel, Jin Tae Kwak, Andre Kadjacsy-Balla, Rohit Bhargava

Proceedings Volume 9791, 97911D (2016) https://doi.org/10.1117/12.2217341

KEYWORDS: FT-IR spectroscopy, Tissues, Imaging spectroscopy, Spectroscopy, Infrared imaging, Pathology, Fourier spectroscopy, Prostate, Tissue optics, Gold, Infrared spectroscopy, Infrared radiation, Data modeling

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Proceedings Article | 19 March 2015 Paper

Nucleus detection using gradient orientation information and linear least squares regression

Jin Tae Kwak, Stephen Hewitt, Sheng Xu, Peter Pinto, Bradford Wood

Proceedings Volume 9420, 94200N (2015) https://doi.org/10.1117/12.2081413

KEYWORDS: Image segmentation, Tissues, RGB color model, Image analysis, Cancer, Pathology, Prostate, Chemical analysis, Medical imaging, Image quality

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Proceedings Article | 11 April 2014 Paper

A multiview boosting approach to tissue segmentation

Jin Tae Kwak, Sheng Xu, Peter Pinto, Baris Turkbey, Marcelino Bernardo, Peter Choyke, Bradford Wood

Proceedings Volume 9041, 90410R (2014) https://doi.org/10.1117/12.2043966

KEYWORDS: Tissues, Image segmentation, Prostate, Feature extraction, Pathology, Prostate cancer, RGB color model, Cancer, Visualization, Receivers

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Showing 5 of 14 publications

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