Dr. Kyongtae Ty Bae Profile

Dr. Kyongtae Ty Bae

Professor at UPMC Presbyterian

SPIE Involvement:

Author

Publications (17)

Proceedings Article | 28 March 2013 Paper

Model-based Bayesian inference for ROC data analysis

Tianhu Lei, K. Ty Bae

Proceedings Volume 8673, 86731D (2013) https://doi.org/10.1117/12.2000669

KEYWORDS: Data modeling, Bayesian inference, Model-based design, Monte Carlo methods, Statistical analysis, Electronic filtering, Statistical modeling, Diagnostics, Autoregressive models, Data analysis

Read Abstract +

Proceedings Article | 28 March 2013 Paper

Deviance statistics in model fit and selection in ROC studies

Tianhu Lei, K. Ty Bae

Proceedings Volume 8673, 86731A (2013) https://doi.org/10.1117/12.2000672

KEYWORDS: Statistical modeling, Data modeling, Electronic filtering, Digital image correlation, Statistical analysis, Adaptive optics, Bayesian inference, Model-based design, Monte Carlo methods, Data analysis

Read Abstract +

Proceedings Article | 14 April 2012 Paper

A new methodology for phase-locking value: a measure of true dynamic functional connectivity

Tianhu Lei, K. Ty Bae, Timothy P. Roberts

Proceedings Volume 8317, 83170T (2012) https://doi.org/10.1117/12.912725

KEYWORDS: Signal to noise ratio, Interference (communication), Phase measurement, Statistical analysis, Mode locking, Brain, Convolution, Signal analyzers, Magnetoencephalography, Wavelets

Read Abstract +

Proceedings Article | 13 March 2010 Paper

Segmentation of blood clot from CT pulmonary angiographic images using a modified seeded region growing algorithm method

Bumwoo Park, Alessandro Furlan, Amol Patil, Kyongtae Bae

Proceedings Volume 7623, 76234K (2010) https://doi.org/10.1117/12.844213

KEYWORDS: Image segmentation, Computed tomography, Signal attenuation, Angiography, Blood, Image processing, Clinical trials, Veins, Spherical lenses, Arteries

Read Abstract +

Pulmonary embolism (PE) is a medical condition defined as the obstruction of pulmonary arteries by a blood clot, usually originating in the deep veins of the lower limbs. PE is a common but elusive illness that can cause significant disability and death if not promptly diagnosed and effectively treated. CT Pulmonary Angiography (CTPA) is the first line imaging study for the diagnosis of PE. While clinical prediction rules have been recently developed to associate short-term risks and stratify patients with acute PE, there is a dearth of objective biomarkers associated with the long-term prognosis of the disease. Clot (embolus) burden is a promising biomarker for the prognosis and recurrence of PE and can be quantified from CTPA images. However, to our knowledge, no study has reported a method for segmentation and measurement of clot from CTPA images. Thus, the purpose of this study was to develop a semi-automated method for segmentation and measurement of clot from CTPA images. Our method was based on Modified Seeded Region Growing (MSRG) algorithm which consisted of two steps: (1) the observer identifies a clot of interest on CTPA images and places a spherical seed over the clot; and (2) a region grows around the seed on the basis of a rolling-ball process that clusters the neighboring voxels whose CT attenuation values are within the range of the mean ± two standard deviations of the initial seed voxels. The rollingball propagates iteratively until the clot is completely clustered and segmented. Our experimental results revealed that the performance of the MSRG was superior to that of the conventional SRG for segmenting clots, as evidenced by reduced degrees of over- or under-segmentation from adjacent anatomical structures. To assess the clinical value of clot burden for the prognosis of PE, we are currently applying the MSRG for the segmentation and volume measurement of clots from CTPA images that are acquired in a large cohort of patients with PE in an on-going NIH-sponsored clinical trial.

Proceedings Article | 27 March 2009 Paper

Simultaneous 3D segmentation of three bone compartments on high resolution knee MR images from osteoarthritis initiative (OAI) using graph cuts

Hackjoon Shim, C. Kent Kwoh, Il Dong Yun, Sang Uk Lee, Kyongtae Bae

Proceedings Volume 7259, 72593P (2009) https://doi.org/10.1117/12.812487

KEYWORDS: Image segmentation, Bone, Magnetic resonance imaging, Cartilage, Image resolution, Tissues, 3D image processing, Pathophysiology, Image processing, Radiography

Read Abstract +

Proceedings Article | 27 March 2009 Paper

Automatic bone registration in MR knee images for cartilage morphological analysis

Ji Hyun Yoo, Soo Kyung Kim, Helen Hong, Hackjoon Shim, C. Kent Kwoh, Kyongtae Bae

Proceedings Volume 7259, 72592H (2009) https://doi.org/10.1117/12.811612

KEYWORDS: Cartilage, Bone, Image registration, Magnetic resonance imaging, Image segmentation, Image fusion, Distance measurement, Morphological analysis, Visualization, 3D image processing

Read Abstract +

Proceedings Article | 26 March 2008 Paper

Segmentation and volumetric measurement of renal cysts and parenchyma from MR images of polycystic kidneys using multi-spectral analysis method

K. Bae, P. Commean, B. Brunsden, D. Baumgarten, B. King, L. Wetzel, P. Kenney, A. Chapman, V. Torres, J. Grantham, L. Guay-Woodford, C. Tao, J. Miller, C. Meyers, W. Bennett

Proceedings Volume 6914, 691449 (2008) https://doi.org/10.1117/12.770934

KEYWORDS: Image segmentation, Kidney, Magnetic resonance imaging, Tissues, Image registration, Image processing, Image classification, Analytical research, Neuroimaging, Brain

Read Abstract +

Proceedings Article | 11 March 2008 Paper

3-D segmentation of articular cartilages by graph cuts using knee MR images from osteoarthritis initiative

Hackjoon Shim, Soochan Lee, Bohyeong Kim, Cheng Tao, Samuel Chang, Il Dong Yun, Sang Uk Lee, Kent Kwoh, Kyongtae Bae

Proceedings Volume 6914, 691448 (2008) https://doi.org/10.1117/12.770887

KEYWORDS: Image segmentation, Cartilage, Magnetic resonance imaging, Tissues, Image processing, Bone, 3D image processing, Radiography, X-rays, Image analysis

Read Abstract +

Proceedings Article | 12 April 2005 Paper

Segmentation of breast ultrasound lesion boundary using texture-based multiresolution method

Kwang Kim, Jong Hyo Kim, Byoung Gu Min, Kyongtae Bae

Proceedings Volume 5750, (2005) https://doi.org/10.1117/12.595936

KEYWORDS: Image segmentation, Breast, Ultrasonography, Image processing, Image resolution, Binary data, Mammography, Mathematical modeling, Image analysis, Solids

Read Abstract +

Computer-aided characterization of a breast ultrasound lesion involves two steps: first, extracting features from the lesion whose boundary is pre-defined on the images, and then converting the features into mathematical models. Most methods assume that the boundaries of the lesions are pre-selected or outlined by sonographers or operators, because automated delineation of lesion boundary is not trivial and is a challenging task. The purpose of this study was to develop and evaluate an automated lesion boundary segmentation method that is based on texture-based, multi-resolution image analysis. One hundred ninety-seven breast ultrasound images containing solid breast lesions from 172 women (age 24-89 years, mean 38 years) were studied. Fifty-five of the 197 images were from 40 women with malignant lesions, and the remaining 142 were from 132 patients with benign lesions. Each breast lesion was identified by an operator who placed a rectangular region of interest (ROI) to widely encompass the lesion. The resolution of the image was compressed, at variable ratios depending on the ROI size, to reduce noise. Texture momentum was computed. A binary image was generated from the texture and pixel intensity parameters. Initial seed boundary was segmented from the binary image and then expanded to the original resolution using the boundary pixel intensity gradient information. The boundary of each breast lesion was delineated by a breast-imaging radiologist who was blinded to the computer-detected lesion boundary. The 'area match ratio' between the manually drawn boundaries and the automatically detected boundaries was computed. This ratio is equal to or less than unity (unity indicates that the areas match exactly). Overall, good agreement was seen between the multi-resolution segmentation method and the radiologist’s manual delineation. The mean area match ratio was 0.87 ±0.02. We have developed a multi-resolution, texture-based method to segment the boundary of breast lesions. This method will facilitate full automation for the characterization of breast ultrasound lesions.

Proceedings Article | 15 May 2003 Paper

Effect of the number of cases in image database on the performance of computer-aided diagnosis (CAD) for the detection of pulmonary nodules in chest radiographs

Junji Shiraishi, Hiroyuki Abe, Roger Engelmann, Kyongtae Bae, Kunio Doi

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480234

KEYWORDS: Databases, Computer aided diagnosis and therapy, Lung, Computer aided design, Chest imaging, Digital imaging, Chest, Medical imaging, Image segmentation, Radiology

Read Abstract +

Proceedings Article | 15 May 2003 Paper

Automated detection of polyps from multislice CT images using 3D morphologic matching algorithm: phantom study

Yonghum Na, Jin Sung Kim, Bruce Whiting, Kyongtae Bae

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480829

KEYWORDS: Computed tomography, Colon, 3D image processing, Computer aided diagnosis and therapy, Image segmentation, Image processing, Detection and tracking algorithms, Collimation, Latex, Ultrasonography

Read Abstract +

Proceedings Article | 9 May 2002 Paper

Segmentation of ECG-gated multidetector row-CT cardiac images for functional analysis

Jin Sung Kim, Yonghum Na, Kyongtae Bae

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467142

KEYWORDS: Image segmentation, Computed tomography, 3D image processing, Principal component analysis, Functional analysis, Heart, 3D modeling, Sensors, Temporal resolution, Image analysis

Read Abstract +

Proceedings Article | 7 August 2001 Paper

Workstation acquisition node for multicenter imaging studies

Stephen Moore, David Maffitt, G. James Blaine, Kyongtae Bae

Proceedings Volume 4323, (2001) https://doi.org/10.1117/12.435489

KEYWORDS: Data centers, Image transmission, Internet, Human-machine interfaces, Switches, Data modeling, Scanners, Data acquisition, Image processing, Image storage

Read Abstract +

Proceedings Article | 1 May 1991 Paper

Visualization of liver in 3-D

Chin-Tu Chen, Jin-Shin Chou, Maryellen Giger, Charles Kahn, Kyongtae Bae, Wei-Chung Lin

Proceedings Volume 1444, (1991) https://doi.org/10.1117/12.45193

KEYWORDS: Liver, Visualization, Image segmentation, 3D image processing, 3D visualizations, Volume rendering, Surgery, Image analysis, X-ray computed tomography, Magnetic resonance imaging

Read Abstract +

Proceedings Article | 1 April 1991 Paper

Automatic acquisition of movement information by a knowledge-based recognition approach

Kyongtae Bae, Martin Altschuler

Proceedings Volume 1380, (1991) https://doi.org/10.1117/12.48077

KEYWORDS: Data modeling, Image segmentation, 3D modeling, Image processing, Motion models, Light emitting diodes, 3D image processing, Data acquisition, 3D acquisition, Biostereometrics

Read Abstract +

Proceedings Article | 1 April 1991 Paper

High-resolution fully 3-D mapping of human surfaces by laser array camera and data representations

Kyongtae Bae, Martin Altschuler

Proceedings Volume 1380, (1991) https://doi.org/10.1117/12.48080

KEYWORDS: Cameras, Calibration, 3D image processing, Data acquisition, 3D metrology, Binary data, Biomedical optics, Imaging systems, Image processing, Projection systems

Read Abstract +

Proceedings Article | 1 March 1991 Paper

Three-dimensional reconstruction of liver from 2-D tomographic slices

Jin-Shin Chou, Chin-Tu Chen, Maryellen Giger, Charles Kahn, Kyongtae Bae, Wei-Chung Lin

Proceedings Volume 1396, (1991) https://doi.org/10.1117/12.47736

KEYWORDS: Liver, 3D image processing, Image segmentation, 3D image reconstruction, 3D displays, Volume rendering, Visualization, Image visualization, Tomography, Computed tomography

Read Abstract +

Showing 5 of 17 publications

Conference Committee Involvement (25)

Image Processing

11 February 2018 | Houston, Texas, United States

Image Processing Posters

12 February 2017 | Orlando, FL, United States

Image Processing

12 February 2017 | Orlando, Florida, United States

Image Processing

1 March 2016 | San Diego, California, United States

Computer-Aided Diagnosis

28 February 2016 | San Diego, California, United States

Image Processing

24 February 2015 | Orlando, Florida, United States

Computer-Aided Diagnosis

22 February 2015 | Orlando, Florida, United States

Computer-Aided Diagnosis

18 February 2014 | San Diego, California, United States

Image Processing

16 February 2014 | San Diego, California, United States

Computer-Aided Diagnosis

12 February 2013 | Lake Buena Vista (Orlando Area), Florida, United States

Image Processing

10 February 2013 | Lake Buena Vista (Orlando Area), Florida, United States

Computer-Aided Diagnosis

7 February 2012 | San Diego, California, United States

Image Processing

6 February 2012 | San Diego, California, United States

Computer-Aided Diagnosis

15 February 2011 | Lake Buena Vista (Orlando), Florida, United States

Image Processing

14 February 2011 | Lake Buena Vista (Orlando), Florida, United States

Computer-Aided Diagnosis

16 February 2010 | San Diego, California, United States

Image Processing

14 February 2010 | San Diego, California, United States

Computer-Aided Diagnosis

10 February 2009 | Lake Buena Vista (Orlando Area), Florida, United States

Image Processing

8 February 2009 | Lake Buena Vista (Orlando Area), Florida, United States

Computer-Aided Diagnosis

19 February 2008 | San Diego, California, United States

Image Processing

17 February 2008 | San Diego, California, United States

Computer-Aided Diagnosis

20 February 2007 | San Diego, CA, United States

Image Processing

18 February 2007 | San Diego, CA, United States

Image Processing

13 February 2006 | San Diego, California, United States

Physiology and Function: Methods, Systems, and Applications

16 February 2003 | San Diego, California, United States

Showing 5 of 25 Conference Committees

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years