Conference

Conference Paper and Peer-Reviewed Presentation

[C44] Mohsen Hariri, Prathyush Chirra, Malhar Patel, Tal Tiano Einat, Ittai Dayan, Alex Tonetti, Yuval Baror, Mathias Blom, Tristan Barrett, Nikita Sushentsev, Joshua D. Kaggie, Shuaiyu Yuan, Dufan Wu, Baihui Yu, Zhiliang Lyu, Cheyu Hsu, Weichung Wang, Smitha Krishnamurthi, and Satish E. Viswanath.

Federated Image Quality Assessment of Prostate Mri Scans in a Multi-institutional Setting.

AACR Annual Meeting, 2024.

[C43] Po-Ting Chen, Dawei Chang, Pochuan Wang, Kao-Lang Liu, Holger Roth, Wei-Chih Liao, Weichung Wang.

Analysis of Pre-diagnostic Ct Images With Artificial Intelligence Facilitates Early Detection of Pancreatic Cancer.

Radiological Society of North America Annual Meeting (RSNA), 2023.

[C42] Helin Ku, Cheyu Hsu, Weichung Wang, Chunhao Chang, Shihmin Lin, Rouyi Chen, Hsinhan Tsai.

Pioneering a Multi-Modal Deep Learning Approach for Hypopharyngeal Cancer Segmentation: Comprehensive Evaluation and Performance Analysis using Diverse MRI Data Across Multiple Institutions.

Radiological Society of North America Annual Meeting (RSNA), 2023.

[C41] Tianyu Hwang, Chih-Hung Wang, Holger R. Roth, Dong Yang, Can Zhao, Chien-Hua Huang, Weichung Wang*.

Semi-supervised Learning with Contrastive and Topology Losses for Catheter Segmentation and Misplacement Prediction.

Medical Imaging with Deep Learning  (MIDL), 2023.

[C40] Cheyu Hsu and Weichung Wang. 

Multi-modality Epidermal Growth Factor Receptor Mutation Associated Radiographic Phenotype Predicts Lesion-wise Progression of Brain Metastases from Non-small Cell Lung Cancer after Upfront Radiosurgery.

Radiological Society of North America Annual Meeting (RSNA), 2022.

[C39] Po-Ting Chen, Wei-Chih Liao, Dawei Chang, Pochuan Wang, Kao-Lang Liu, Ming-Shiang Wu, Weichung Wang.

External Validation of Pancreatic Cancer Detection on CT with A Computer-aided Detection Tool Combining Radiomics and Deep Learning Models

Radiological Society of North America Annual Meeting (RSNA), 2022.

[C38 ] Chen Shen, Pochuan Wang, Dong Yang, Daguang Xu, Masahiro Oda, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Chiou-Shann Fuh, Kensaku Mori, Weichung Wang* and Holger R. Roth.

Joint Multi Organ and Tumor Segmentation from Partial Labels Using Federated Learning.

International Workshop on Distributed, Collaborative, and Federated Learning, 2022.

https://doi.org/10.1007/978-3-031-18523-6_6

[C37] Wei-Chih Liao, Dawei Chang, Po-Ting Chen, Pochuan Wang, Kao-Lang Liu, Ming-Shiang Wu, Weichung Wang.

Distinguishing Pancreatic Cancer From Non-cancerous Pancreatic Diseases and Normal Pancreas With Deep Learning-based Segmentation and Radiomics-based Classification.

Digestive Disease Week (DDW), ePoster, May 2022.

[C36] Cheyu Hsu, Chunhao Chang, Tom Weiwu Chen, Hsinhan Tsai, Shihchieh Ma, Weichung Wang*.

Brain Tumor Segmentation (BraTS) Challenge Short Paper: Improving Three-Dimensional Brain Tumor Segmentation Using SegResnet and Hybrid Boundary-Dice Loss.

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 7th International Workshop, BrainLes 2021

https://doi.org/10.1007/978-3-031-09002-8_30

[C35]  Jun-Ting Chen, Yu-Cheng Huang, Holger Roth, Dong Yang, Chih-Kuo Lee, Wen-Jeng Lee, Tzung-Dau Wang, Cheng-Ying Chou, and Weichung Wang*.  

Detection and Classification of Coronary Artery Plaques in Coronary Computed Tomography Angiography Using 3D CNN.

The 12th Workshop on Statistical Atlases and Computational Modelling of the Heart (STACOM 2021). Lecture Notes in Computer Science, Vol 13131, Springer. 

https://doi.org/10.1007/978-3-030-93722-5_23

[C34] Chen Shen, Pochuan Wang, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Weichung Wang*, Chiou-Shann Fuh, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, and Kensaku Mori. 

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation.

MICCAI Workshop on Distributed and Collaborative Learning, September 2021.

[C33] Wei-Chih Liao*, Po-Ting Chen, Tinghui Wu, Dawei Chang, Pochuan Wang, Kao-Lang Liu, Ming-Shiang Wu, Weichung Wang*. 

Pancreas Segmentation and Pancreatic Cancer Detection on CT With Deep Learning

Digestive Disease Week (DDW), Oral Presentation, May 2021.

[C32] Po-Ting Chen, Pochuan Wang, Tinghui Wu, Dawei Chang, Holger R. Roth, Kao-Lang Liu, Wei-Chih Liao, Weichung Wang.

Adrenal Gland Segmentation on Abdominal CT Images Using Deep Learning.

International Forum on Medical Imaging in Asia (IFMIA), 2021.

Abstract.

[C31] Chao-Jung Huang, Tinghui Wu, Jui-Ting Lu, Beatrice Lin, Dawei Chang, Pochuan Wang, Mei-Chi Wang, Peijung Lee, Weichung Wang.

Developing a Medical Artificial Intelligence Course for High School Students.

International Forum on Medical Imaging in Asia (IFMIA), 2021.

https://doi.org/10.1117/12.2590769

Abstract.

[C30] Wei-Chih Liao, Po-Ting Chen, Hui-Hsuan Yen, Dawei Chang, Kao-Lang Liu, Su-Yun Huang, Holger Roth, Ming-Shiang Wu, Weichung Wang.

Radiomic Features Distinguish Pancreatic Cancer From Non-cancerous Pancreas.

Digestive Disease Week (DDW), Oral Presentation, 2020.

[C29] C Lee, C Hsu, Y Lee, P Wang, H R Roth, W Wang.

Three Dimensional Brain Metastases Segmentation Using Coarse-to- Fine Neural Architecture Search with Boundary Loss.

Radiological Society of North America Annual Meeting (RSNA), 2020.

[C28] Pochuan Wang*, Chen Shen, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Kazunari Misawa, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Weichung Wang, and Kensaku Mori.

Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning.

MICCAI Workshop on Distributed and Collaborative Learning, October 2020.

[C27] Feng-Mao Lin, Chi-Wen Chen, Wei-Da Huang, Liangtsan Wu, Anthony Costa, Eric K. Oermann and Weichung Wang.

Constructing a Platform based on Deep Learning Model to Mimic the Self-Organization Process of CT Images Order for Automatically Recognizing Human Anatomy.

Radiological Society of North America (RSNA), December, 2019.

[C26] Po-Ting Chen, Huihsuan Yen, Dawei Chang, Wei-Chih Liao, Kao-Lang Liu, Holger R. Roth, Weichung Wang, Tinghui Wu.

Differentiation between Pancreatic Cancer and Nontumorous Pancreas on Computed Tomography by Radiomics and Machine Learning.

Radiological Society of North America (RSNA), December, 2019.

[C25] Shihmin Lin, Cheyu Hsu, Yuehchou Lee, T. Li, S. Kuo, Weichung Wang.

Efficacy Evaluation of Optimal Patient Selection for Hypopharyngeal Cancer Organ Preservation Therapy using MRI-derived Radiomic Signature: Bi-institutional Propensity Score Matched Analysis.

European Society for Medical Oncology (ESMO) Congress, October, 2019.

[C24] Cheyu Hsu, S. Kuo, Weichung Wang, T.W. Chen, Yuehchou Lee.

Radiographic Phenotyping to Identify Intracranial Disseminated Recurrence in Brain metastases Treated With Radiosurgery Using Contrast-enhanced MR Imaging.

European Society for Medical Oncology (ESMO) Congress, October, 2019.

[C23] Chiatse Wang, Chih-Kuo Lee, Yu-Cheng Huang, Wen-Jeng Lee, Tzung-Dau Wang, Weichung Wang, Cheng-Ying Chou, Junting Chen, Weidao Lee.

Severe Stenosis Detection using 2D Convolutional Recurrent Network.

European Society of Cardiology (ESC) Congress, September, 2019.

[C22] Wei-Chih Liao, Wei-Chung Wang, Ting-Hui Wu, Kao-Lang Liu, Po-Ting Chen, Hui-Hsuan Yen, Holger R. Roth.

Differentiation Between Pancreatic Cancer and Normal Pancreas on Computed Tomography with Artificial Intelligence.

Digestive Disease Week (DDW), May, 2019.

[C21] Hartwig Anzt, Yen-Chen Chen, Terry Cojean, Jack Dongarra, Goran Flegar, Pratik Nayak, Enrique S. Quintana-Orti, Yuhsiang M. Tsai, and Weichung Wang.

Towards Continuous Benchmarking: An Automated Performance Evaluation Framework for High Performance Software.

The Platform for Advanced Scientific Computing, 2019.

[C20] Mu Yang, Ray-Bing Chen, I-Hsin Chung, and Weichung Wang.

Particle Swarm Stepwise Algorithm (PaSS) on Multicore Hybrid CPU-GPU Clusters.

The IEEE CIT, 2016.

[C19] Chien-Min Kao, Heejong Kim, Chang-Han Huang, Cheng-Ying Chou, Weichung Wang, and Chin-Tu Chen.

A continuous-coordinate image reconstruction method for list-mode time-of-flight position emission tomography.

IEEE Nuclear Science Symposium and Medical Imaging Conference, 2013.

[C18] Yu-Fen Cheng, Tsung-Ming Huang, Feng-Nan Hwang, and Weichung Wang.

A two-level polynomial Jacobi-Davidson algorithm for cubic acoustic eigenvalue problems.

21st International Conference on Domain Decomposition Methods, INRIA Rennes-Bretagne-Atlantique, 2012.

[C17] Yaohung M. Tsai, Ray-Bing Chen, and Weichung Wang.

Tuning Block Size for QR Factorization on CPU-GPU Hybrid Systems.

Special Session: Auto-Tuning for Multicore and GPU (ATMG) in Conjunction with the IEEE 6th International Symposium on Embedded Multicore SoCs, Aizu-Wakamatsu, Japan, 2012.

[C16] Chih-Kang Huang, Weichung Wang, Kai-Yuan Tzen, Win-Li Lin, Cheng-Ying Chou.

FDOPA kinetics analysis in PET images for Parkinson’s disease diagnosis by use of particle swarm optimization.

IEEE International Symposium on Biomedical Imaging, 2012.

[C15] Z.-H. Wei, F.-N. Hwang, T.-M. Huang, and W. Wang.

A parallel scalable PETSc-based Jacobi-Davidson polynomial eigensolver with application in quantum dot simulation.

Lecture Notes in Computational Science and Engineering, Vol. 78, pp. 157-164, 2011.

[C14] Yae-Lin Sheu, Weichung Wang, Yukai Hung, Pai-Chi Li.

Photoacoustic image reconstruction for linear scanning geometry using particle swarm optimization with a K-space simulation scheme.

SPIE Photonics West, San Francisco, USA, 2010.

[C13] Wenli Tsou, Weichung Wang, Yannjiun Tzeng.

Applying Computer Multimedia Storytelling Website in Foreign Language Learning.

3rd IEEE International Conference on Advanced Learning Technologies, pp. 262-263, Athens, Greece, 2003.

[C12] Pofen Wang, Wenlung Cheng, Weichung Wang, and Pi-hsia Hung.

An Elementary School Mathematics Dynamic Learning System and Its Effects.

Computers in Education, International Conference, by IEEE Computer Society, pp. 806-807, 2002.

[C11] Shuhsiang Wang, Weichung Wang, Qui-Ming Huang.

Using Computers as Mindtools to Learn Time Concept in Elementary School.

Computers in Education, International Conference, by IEEE Computer Society, pp. 808-812, 2002.

[C10] ChienhsunTseng, Weichung Wang, Yijinn Lin, Pi-hsia Hung.

Effects of Computerized Advance Organizers on Elementary Chienhsun School Mathematics Learning.

Computers in Education, International Conference, by IEEE Computer Society, pp. 838-839, 2002.

[C9] Weichung Wang, Chienhsun Tseng, and Shiantang Huang.

Using Subsumption Theory Based Computer Mindtools to Assist Pupils in Constructing Probability Concept.

Proceedings of ICCE/SchoolNet, Volume 1, 106-113, 2001.

[C8] Weichung Wang, Shuhsiang Wang, and Kunhui Lee.

The Effects of Learning Speed Concept with Computers in Elementary School.

Proceedings of ICCE/SchoolNet, Volume 2, pp. 1097-1104, 2001.

[C7] Weichung Wang, Pofen Wang, and Yinghsiu Chung.

Computer Based Situated Learning in Elementary School Statistics.

Proceedings of ICCE/SchoolNet, Volume 3, pp. 267-1274, 2001.

[C6] 王偉仲, 鐘瑩修, 王珀芬.

應用情境學習與心智工具輔助國小學童學習統計概念.

第五屆全球華人學習科技研討會暨第十屆國際電腦輔助教學研討會大會論文集, pp. 419-426, 2001.

[C5] 王偉仲, 李昆輝, 王淑湘.

以電腦做為心智工具輔助國小學童學習速率的概念.

第五屆全球華人學習科技研討會暨第十屆國際電腦輔助教學研討會大會論文集, pp. 909-916, 2001.

[C4] 王偉仲, 黃湘婷, 曾建勳.

電腦視覺化模擬情境在國小機率問題解決之輔助學習.

第五屆全球華人學習科技研討會暨第十屆國際電腦輔助教學研討會大會論文集, pp. 479-486, 2001.

[C3] Weichung Wang, Yannjiun Tzeng, and Yuan Chen.

A Comparative Study of Applying Internet on Cooperative and Traditional Learning,Proceedings of the International Conference on Computers in Education.

International Conference on Computer-Assisted Instruction, Volume 1, pp. 207-214, 2000.

[C2] Weichung Wang, Shiru Chern, and Chiaming Liang.

Building Mathematics Collaborative Learning Web Sites, Proceedings of the International Conference on Computers in Education.

International Conference on Computer-Assisted Instruction, Volume 1, pp. 294-297, 2000.

[C1] Weichung Wang and Tainshu Ma.

Which Chinese input method is more suitable for sixth-grade pupils? keyboarding or non-keyboarding.

Proceedings of the International Conference on Computers in Education / International Conference on Computer-Assisted Instruction, Volume 1, pp. 379-382, 2000.