Biomedical signal processing

Wordcloud image generated by research papers on biomedical signal processing, Machine Intelligence Lab

PNI (perineural invasion) Detection

  • Youngjae Park, Jinhee Park, Gil-Jin Jang. Efficient Perineural Invasion Detection of Histopathological Images Using U-Net. Electronics (MDPI). Electronics 2022, 11(10), 1649. https://doi.org/10.3390/electronics11101649

    • Proposed an efficient U-Net architecture and boundary dilation methods for boundary detection.

Ongoing research: Cervical cancer

  • Jung Kweon Bae, Hyun-Jin Roh, Joon S You, Kyungbin Kim, Yujin Ahn, Sanzhar Askaruly, Kibeom Park, Hyunmo Yang, Gil-Jin Jang, Kyung Hyun Moon, Woonggyu Jung*. Quantitative Screening of Cervical Cancers for Low-Resource Settings: Pilot Study of Smartphone-Based Endoscopic Visual Inspection After Acetic Acid Using Machine Learning Techniques. JMIR mHealth and uHealth. 2020 Mar 11;8(3):e16467. pp 1-15, March 2020

  • Paper in first revision.

  • https://www.kaggle.com/competitions/intel-mobileodt-cervical-cancer-screening/data

Ongoing research: EEG, Alzheimer’s disease

  • Paper in second revision.

DCE-MRI tumor

  • S. H. Han, E. Ackerstaff, R. Stoyanova, S.Carlin, W. Huang, J. A. Koutcher, J. K. Kim, G.Cho, A. Jo, G. Jang, and H. Cho. Gaussian Mixture Model-based Classification of DCE-MRI data For Identifying Diverse Tumor Microenvironments: Preliminary Results. NMR in Biomedicine, Volume 26, Issue 5, pages 519–532, May 2013.

DCE-MRI image example


Different observations

Hypoxia / necrosis / perfusion

2D plots

Hypoxia / necrosis / perfusion

Automatic clustering results

Glaucoma, visual field, variational Bayesian ICA

  • Michael H. Goldbaum, Gil-Jin Jang, Chris Bowd, Jiucang Hao, Linda M. Zangwill, Jeffrey Liebmann, Christopher Girkin, Tzyy-Ping Jung, Robert N. Weinreb, and Pamela A. Sample. Patterns Of Glaucomatous Visual Field Loss In SITA Fields Automatically Identified Using Independent Component Analysis. Transactions of the American Ophthalmological Society, Volume 107, pages 136-145, December 2009.

  • Michael H Goldbaum, Intae Lee, Giljin Jang, Madhusudhanan Balasubramanian, Pamela A Sample, Robert N Weinreb, Jeffrey M Liebmann, Christopher A Girkin, Douglas R Anderson, Linda M Zangwill, Marie-Josee Fredette, Tzyy-Ping Jung, Felipe Medeiros, and Christopher Bowd. Progression of Patterns (POP): A Machine Classifier Algorithm to Identify Glaucoma Progression in Visual Fields. Investigative Ophthalmology & Visual Science. 2012 Sep 25;53(10):6557-67. Print 2012 Oct.

  • Christopher Bowd, Robert N. Weinreb, Madhusudhanan Balasubramanian, Intae Lee, Giljin Jang, Siamak Yousefi, Linda M. Zangwill, Felipe A. Medeiros, Christopher A. Girkin, Jeffrey M. Liebmann, Michael H. Goldbaum. Glaucomatous Patterns in Frequency Doubling Technology (FDT) Perimetry Data Identified by Unsupervised Machine Learning Classifiers. PLOS ONE, Volume 9, Issue 1, January 2014