Search Results for author: Chang-Fu Kuo

Found 8 papers, 2 papers with code

Lumbar Bone Mineral Density Estimation from Chest X-ray Images: Anatomy-aware Attentive Multi-ROI Modeling

no code implementations5 Jan 2022 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

Osteoporosis is a common chronic metabolic bone disease often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e. g. via Dual-energy X-ray Absorptiometry (DXA).

Density Estimation

Coherence Learning using Keypoint-based Pooling Network for Accurately Assessing Radiographic Knee Osteoarthritis

no code implementations16 Dec 2021 Kang Zheng, Yirui Wang, Chen-I Hsieh, Le Lu, Jing Xiao, Chang-Fu Kuo, Shun Miao

In this work, we propose a computer-aided diagnosis approach to provide more accurate and consistent assessments of both composite and fine-grained OA grades simultaneously.

Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray

no code implementations5 Apr 2021 Fakai Wang, Kang Zheng, Yirui Wang, XiaoYun Zhou, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

In this paper, we propose a method to predict BMD from Chest X-ray (CXR), one of the most common, accessible, and low-cost medical image examinations.

Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images

no code implementations24 Mar 2021 Kang Zheng, Yirui Wang, XiaoYun Zhou, Fakai Wang, Le Lu, ChiHung Lin, Lingyun Huang, Guotong Xie, Jing Xiao, Chang-Fu Kuo, Shun Miao

Specifically, we propose a new semi-supervised self-training algorithm to train the BMD regression model using images coupled with DEXA measured BMDs and unlabeled images with pseudo BMDs.

Density Estimation

Contour Transformer Network for One-shot Segmentation of Anatomical Structures

1 code implementation2 Dec 2020 Yuhang Lu, Kang Zheng, Weijian Li, Yirui Wang, Adam P. Harrison, ChiHung Lin, Song Wang, Jing Xiao, Le Lu, Chang-Fu Kuo, Shun Miao

In this work, we present Contour Transformer Network (CTN), a one-shot anatomy segmentation method with a naturally built-in human-in-the-loop mechanism.

One-Shot Learning One-Shot Segmentation

exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources

no code implementations Findings of the Association for Computational Linguistics 2020 Wen Tai, H. T. Kung, Xin Dong, Marcus Comiter, Chang-Fu Kuo

We introduce exBERT, a training method to extend BERT pre-trained models from a general domain to a new pre-trained model for a specific domain with a new additive vocabulary under constrained training resources (i. e., constrained computation and data).

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