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Your search keyword '"Chai, Jyh-Wen"' showing total 240 results
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240 results on '"Chai, Jyh-Wen"'

12. Assessment of Prostate Volume and Prostate-specific Antigen Density With the Segmentation Method on Magnetic Resonance Imaging

Author

LIN, YEN-TING, HUNG, SIU-WAN, CHIU, KUN-YUAN, CHAI, JYH-WEN, and LIN, JIN-CHING

Subjects
Pharmacology, Cancer Research, General Biochemistry, Genetics and Molecular Biology, Research Article
Abstract

Background/Aim: This study aimed to compare the prostate volume (PV) and prostate-specific antigen density (PSAD) obtained using the ellipsoid volume formula or segmentation methods on magnetic resonance imaging (MRI) and further predict prostate cancer (PCa). Patients and Methods: Retrospectively, the enrolled patients underwent prostate MRI and had PSA levels between 4 and 10 ng/ml. The PV was measured with both the ellipsoid volume formula (PVe) and the segmentation method (PVs). The transitional zone volume (TZV) was measured with the segmentation method. The PSADe, PSADs, and PSAD_TZV were calculated. Bland-Altman plots were used to compare the agreements. ROC curve analysis was used to compare the diagnostic accuracies to predict PCa. The results were also compared between the PCa and the no-PCa groups, and among tumors with different locations and different Gleason scores (GS). Results: Seventy-six of the 117 enrolled patients were classified into the PCa group. There were high agreements between PVs and PVe as well as between PSADs and PSADe, while several outliers were mainly due to post-transurethral resection of the prostate changes and irregular hyperplastic nodules. The diagnostic accuracy of PSADe (AUC: 0.732) was slightly higher than that of PSADs (AUC: 0.729) and PSAD_TZV (AUC: 0.715). The PSADe and PSADs were not different among different tumor locations but were higher in GS ≥7 lesions (both p=0.006). Conclusion: The segmentation method can be an alternative method to measure PV and calculate PSAD before prostate biopsy, particularly in post-transurethral resection of the prostate patients or those with irregular hyperplastic nodules.

Published
2023

21. Supplemental Material - Cortical thickness and diffusion tensor imaging in patients with neuropsychiatric systemic lupus erythematosus, with normal structure on brain MRI

Author

Liang, Shao-Yen, Wu, Yi-Ying, Chang, Ni-Jung, Lai, Kuo-Lung, Chen, Hsian-Min, Chen, Hung-Chieh, Ouyang, Yen-Chieh, Chen, Yi-Ming, and Chai, Jyh-Wen

Subjects
111702 Aged Health Care, FOS: Health sciences
Abstract

Supplemental Material for Cortical thickness and diffusion tensor imaging in patients with neuropsychiatric systemic lupus erythematosus, with normal structure on brain MRI by Shao-Yen Liang, Yi-Ying Wu, Ni-Jung Chang, Kuo-Lung Lai, Hsian-Min Chen, Hung-Chieh Chen, Yen-Chieh Ouyang, Yi-Ming Chen, Jyh-Wen Chai in Lupus

Published
2023
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36. An automatic computer-aided detection system for meniscal tears on magnetic resonance images

Author

Ramakrishna, Bharath, Liu, Weimin, Saiprasad, Ganesh, Safdar, Nabile, Chang, Chein-I, Siddiqui, Khan, Kim, W., Siegel, Eliot, Chai, Jyh-Wen, Chen, Clayton Chi-Chang, and Lee, San-Kan

Subjects
Computer-aided medical diagnosis -- Research, Magnetic resonance imaging -- Methods, Knee -- Injuries, Knee -- Diagnosis, Business, Electronics, Electronics and electrical industries, Health care industry
Published
2009

39. Band expansion-based over-complete independent component analysis for multispectral processing of magnetic resonance images

Author

Ouyang, Yen-Chieh, Chen, Hsian-Min, Chai, Jyh-Wen, Chen, Clayton Chi-Chang, Poon, Sek-Kwong, Yang, Ching-Wen, Lee, San-Kan, and Chang, Chein-I

Subjects
Discriminant analysis -- Methods, Factor analysis -- Methods, Magnetic resonance imaging -- Methods, Image processing -- Technology application, Biomedical engineering -- Research, Technology application, Biological sciences, Business, Computers, Health care industry
Abstract

Independent component analysis (ICA) has found great promise in magnetic resonance (MR) image analysis. Unfortunately, two key issues have been overlooked and not investigated. One is the lack of MR images to be used to unmix signal sources of interest. Another is the use of random initial projection vectors by ICA, which causes inconsistent results. In order to address the first issue, this paper introduces a band-expansion process (BEP) to generate an additional new set of images from the original MR images via nonlinear functions. These newly generated images are then combined with the original MR images to provide sufficient MR images for ICA analysis. In order to resolve the second issue, a prioritized ICA (PICA) is designed to rank the ICA-generated independent components (ICs) so that MR brain tissue substances can be unmixed and separated by different ICs in a prioritized order. Finally, BEP and PICA are combined to further develop a new ICA-based approach, referred to as PICA-BEP to perform MR image analysis. Index Terms--Band-expansion process (BEP), FastICA, independent component analysis (ICA), magnetic resonance (MR) analysis, over-complete ICA (OC-ICA), prioritized ICA (PICA), prioritized ICA band-expansion process (PICA-BEP).

Published
2008

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