no code implementations • 11 Jun 2018 • Dakai Jin, Ziyue Xu, You-Bao Tang, Adam P. Harrison, Daniel J. Mollura
Qualitative results demonstrate the effectiveness of our method compared to the state-of-art.
no code implementations • 19 Mar 2018 • Dakai Jin, Ziyue Xu, Adam P. Harrison, Daniel J. Mollura
Segmentation and quantification of white matter hyperintensities (WMHs) are of great importance in studying and understanding various neurological and geriatric disorders.
no code implementations • 25 Jan 2018 • Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers
Toward this end, we introduce a convolutional neural network based weakly supervised self-paced segmentation (WSSS) method to 1) generate the initial lesion segmentation on the axial RECIST-slice; 2) learn the data distribution on RECIST-slices; 3) adapt to segment the whole volume slice by slice to finally obtain a volumetric segmentation.
no code implementations • 15 Aug 2017 • Kevin George, Adam P. Harrison, Dakai Jin, Ziyue Xu, Daniel J. Mollura
We are the first to apply deep learning to PPLS.
no code implementations • 12 Jun 2017 • Adam P. Harrison, Ziyue Xu, Kevin George, Le Lu, Ronald M. Summers, Daniel J. Mollura
Pathological lung segmentation (PLS) is an important, yet challenging, medical image application due to the wide variability of pathological lung appearance and shape.
no code implementations • 31 Jan 2017 • Holger R. Roth, Le Lu, Nathan Lay, Adam P. Harrison, Amal Farag, Andrew Sohn, Ronald M. Summers
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis.
Ranked #1 on 3D Medical Imaging Segmentation on TCIA Pancreas-CT
no code implementations • 19 Jan 2017 • Mingchen Gao, Ziyue Xu, Le Lu, Adam P. Harrison, Ronald M. Summers, Daniel J. Mollura
Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually delineated regions of interest (ROIs), is a clinically desirable, yet challenging goal.
no code implementations • 25 Jun 2018 • Youbao Tang, Adam P. Harrison, Mohammadhadi Bagheri, Jing Xiao, Ronald M. Summers
Response evaluation criteria in solid tumors (RECIST) is the standard measurement for tumor extent to evaluate treatment responses in cancer patients.
no code implementations • 3 Jul 2018 • Jinzheng Cai, Le Lu, Adam P. Harrison, Xiaoshuang Shi, Pingjun Chen, Lin Yang
Given image labels as the only supervisory signal, we focus on harvesting, or mining, thoracic disease localizations from chest X-ray images.
no code implementations • 2 Jul 2018 • Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers
Volumetric lesion segmentation from computed tomography (CT) images is a powerful means to precisely assess multiple time-point lesion/tumor changes.
no code implementations • 19 Jul 2018 • Yu-Xing Tang, Xiaosong Wang, Adam P. Harrison, Le Lu, Jing Xiao, Ronald M. Summers
In addition, highly confident samples (measured by classification probabilities) and their corresponding class-conditional heatmaps (generated by the CNN) are extracted and further fed into the AGCL framework to guide the learning of more distinctive convolutional features in the next iteration.
no code implementations • 18 Jul 2018 • Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers
The first GAN reduces the noise in the CT image and the second GAN generates a higher resolution image with enhanced boundaries and high contrast.
no code implementations • 4 Sep 2019 • Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P. Harrison, Jing Xiao, Chen-Kan Tseng, Le Lu
Clinical target volume (CTV) delineation from radiotherapy computed tomography (RTCT) images is used to define the treatment areas containing the gross tumor volume (GTV) and/or sub-clinical malignant disease for radiotherapy (RT).
no code implementations • 4 Sep 2019 • Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P. Harrison, Jing Xiao, Chen-Kan Tseng, Le Lu
Gross tumor volume (GTV) segmentation is a critical step in esophageal cancer radiotherapy treatment planning.
no code implementations • 5 Sep 2019 • Bo Zhou, Adam P. Harrison, Jiawen Yao, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu
This is the focus of our work, where we present a principled data curation tool to extract multi-phase CT liver studies and identify each scan's phase from a real-world and heterogenous hospital PACS dataset.
no code implementations • 4 Sep 2019 • Yirui Wang, Le Lu, Chi-Tung Cheng, Dakai Jin, Adam P. Harrison, Jing Xiao, Chien-Hung Liao, Shun Miao
In this paper, we propose a two-stage hip and pelvic fracture detection method that executes localized fracture classification using weakly supervised ROI mining.
no code implementations • CVPR 2020 • Dazhou Guo, Dakai Jin, Zhuotun Zhu, Tsung-Ying Ho, Adam P. Harrison, Chun-Hung Chao, Jing Xiao, Alan Yuille, Chien-Yu Lin, Le Lu
This is the goal of our work, where we introduce stratified organ at risk segmentation (SOARS), an approach that stratifies OARs into anchor, mid-level, and small & hard (S&H) categories.
no code implementations • ECCV 2020 • Fengze Liu, Jingzheng Cai, Yuankai Huo, Chi-Tung Cheng, Ashwin Raju, Dakai Jin, Jing Xiao, Alan Yuille, Le Lu, Chien-Hung Liao, Adam P. Harrison
We extensively evaluate our JSSR system on a large-scale medical image dataset containing 1, 485 patient CT imaging studies of four different phases (i. e., 5, 940 3D CT scans with pathological livers) on the registration, segmentation and synthesis tasks.
no code implementations • ECCV 2020 • Ashwin Raju, Chi-Tung Cheng, Yunakai Huo, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHuang Liao, Adam P. Harrison
In medical imaging, organ/pathology segmentation models trained on current publicly available and fully-annotated datasets usually do not well-represent the heterogeneous modalities, phases, pathologies, and clinical scenarios encountered in real environments.
no code implementations • 28 May 2020 • Ke Yan, Jinzheng Cai, Adam P. Harrison, Dakai Jin, Jing Xiao, Le Lu
First, we learn a multi-head multi-task lesion detector using all datasets and generate lesion proposals on DeepLesion.
Ranked #5 on Medical Object Detection on DeepLesion (using extra training data)
no code implementations • 27 May 2020 • Zhuotun Zhu, Ke Yan, Dakai Jin, Jinzheng Cai, Tsung-Ying Ho, Adam P. Harrison, Dazhou Guo, Chun-Hung Chao, Xianghua Ye, Jing Xiao, Alan Yuille, Le Lu
We focus on the detection and segmentation of oncology-significant (or suspicious cancer metastasized) lymph nodes (OSLNs), which has not been studied before as a computational task.
no code implementations • 28 Jun 2020 • Yuankai Huo, Jinzheng Cai, Chi-Tung Cheng, Ashwin Raju, Ke Yan, Bennett A. Landman, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison
To this end, we propose a fully-automated and multi-stage liver tumor characterization framework designed for dynamic contrast computed tomography (CT).
no code implementations • ECCV 2020 • Haomin Chen, Yirui Wang, Kang Zheng, Weijian Li, Chi-Tung Cheng, Adam P. Harrison, Jing Xiao, Gregory D. Hager, Le Lu, Chien-Hung Liao, Shun Miao
A new contrastive feature learning component in our Siamese network is designed to optimize the deep image features being more salient corresponding to the underlying semantic asymmetries (caused by pelvic fracture occurrences).
no code implementations • 6 Jul 2020 • Yuhang Lu, Weijian Li, Kang Zheng, Yirui Wang, Adam P. Harrison, Chi-Hung Lin, Song Wang, Jing Xiao, Le Lu, Chang-Fu Kuo, Shun Miao
Accurate segmentation of critical anatomical structures is at the core of medical image analysis.
no code implementations • 7 Aug 2020 • Bowen Li, Ke Yan, Dar-In Tai, Yuankai Huo, Le Lu, Jing Xiao, Adam P. Harrison
Ultrasound (US) is a critical modality for diagnosing liver fibrosis.
no code implementations • 30 Aug 2020 • Jinzheng Cai, Ke Yan, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu, Adam P. Harrison
Identifying, measuring and reporting lesions accurately and comprehensively from patient CT scans are important yet time-consuming procedures for physicians.
no code implementations • 29 Aug 2020 • Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo, Ke Yan, Tsung-Ying Ho, Jinzheng Cai, Adam P. Harrison, Xianghua Ye, Jing Xiao, Alan Yuille, Min Sun, Le Lu, Dakai Jin
Specifically, we first utilize a 3D convolutional neural network with ROI-pooling to extract the GTV$_{LN}$'s instance-wise appearance features.
no code implementations • 5 Sep 2020 • Ashwin Raju, Zhanghexuan Ji, Chi Tung Cheng, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison
Mask-based annotation of medical images, especially for 3D data, is a bottleneck in developing reliable machine learning models.
no code implementations • 11 Sep 2020 • Haomin Chen, Shun Miao, Daguang Xu, Gregory D. Hager, Adam P. Harrison
To this end, we present a deep HMLC approach for CXR CAD.
no code implementations • 7 Dec 2020 • Xinyu Zhang, Yirui Wang, Chi-Tung Cheng, Le Lu, Adam P. Harrison, Jing Xiao, Chien-Hung Liao, Shun Miao
Object detection methods are widely adopted for computer-aided diagnosis using medical images.
no code implementations • 24 Mar 2021 • Bolin Lai, YuHsuan Wu, Xiao-Yun Zhou, Peng Wang, Le Lu, Lingyun Huang, Mei Han, Jing Xiao, Heping Hu, Adam P. Harrison
Lesion detection serves a critical role in early diagnosis and has been well explored in recent years due to methodological advancesand increased data availability.
no code implementations • 12 Apr 2021 • Bowen Li, Xinping Ren, Ke Yan, Le Lu, Lingyun Huang, Guotong Xie, Jing Xiao, Dar-In Tai, Adam P. Harrison
Importantly, ADDLE does not expect multiple raters per image in training, meaning it can readily learn from data mined from hospital archives.
no code implementations • 17 Aug 2021 • Chi-Tung Cheng, Jinzheng Cai, Wei Teng, Youjing Zheng, YuTing Huang, Yu-Chao Wang, Chien-Wei Peng, YouBao Tang, Wei-Chen Lee, Ta-Sen Yeh, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison
We develop a flexible three-dimensional deep algorithm, called hetero-phase volumetric detection (HPVD), that can accept any combination of contrast-phase inputs and with adjustable sensitivity depending on the clinical purpose.
no code implementations • 12 Oct 2021 • Bowen Li, Dar-In Tai, Ke Yan, Yi-Cheng Chen, Shiu-Feng Huang, Tse-Hwa Hsu, Wan-Ting Yu, Jing Xiao, Le Lu, Adam P. Harrison
High diagnostic performance was observed across all viewpoints: area under the curves of the ROC to classify >=mild, >=moderate, =severe steatosis grades were 0. 85, 0. 90, and 0. 93, respectively.
no code implementations • 17 Oct 2021 • Peng Wang, YuHsuan Wu, Bolin Lai, Xiao-Yun Zhou, Le Lu, Wendi Liu, Huabang Zhou, Lingyun Huang, Jing Xiao, Adam P. Harrison, Ningyang Jia, Heping Hu
Results: the proposed CAD solution achieves a mean F1 score of 0. 62, outperforming the abdominal radiologist (0. 47), matching the junior hepatology radiologist (0. 61), and underperforming the senior hepatology radiologist (0. 68).
no code implementations • 1 Nov 2021 • Dazhou Guo, Jia Ge, Xianghua Ye, Senxiang Yan, Yi Xin, Yuchen Song, Bing-shen Huang, Tsung-Min Hung, Zhuotun Zhu, Ling Peng, Yanping Ren, Rui Liu, Gong Zhang, Mengyuan Mao, Xiaohua Chen, Zhongjie Lu, Wenxiang Li, Yuzhen Chen, Lingyun Huang, Jing Xiao, Adam P. Harrison, Le Lu, Chien-Yu Lin, Dakai Jin, Tsung-Ying Ho
Accurate organ at risk (OAR) segmentation is critical to reduce the radiotherapy post-treatment complications.
1 code implementation • 12 Feb 2018 • Nathan Lay, Adam P. Harrison, Sharon Schreiber, Gitesh Dawer, Adrian Barbu
We propose random hinge forests, a simple, efficient, and novel variant of decision forests.
1 code implementation • 2 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.
1 code implementation • CVPR 2022 • Wei Zhu, Le Lu, Jing Xiao, Mei Han, Jiebo Luo, Adam P. Harrison
Adversarial domain generalization is a popular approach to DG, but conventional approaches (1) struggle to sufficiently align features so that local neighborhoods are mixed across domains; and (2) can suffer from feature space over collapse which can threaten generalization performance.
1 code implementation • CVPR 2021 • Jinzheng Cai, YouBao Tang, Ke Yan, Adam P. Harrison, Jing Xiao, Gigin Lin, Le Lu
In this work, we present deep lesion tracker (DLT), a deep learning approach that uses both appearance- and anatomical-based signals.
1 code implementation • 7 Apr 2021 • Ashwin Raju, Shun Miao, Dakai Jin, Le Lu, Junzhou Huang, Adam P. Harrison
DISSMs use a deep implicit surface representation to produce a compact and descriptive shape latent space that permits statistical models of anatomical variance.
1 code implementation • 21 Jan 2020 • Jinzheng Cai, Adam P. Harrison, Youjing Zheng, Ke Yan, Yuankai Huo, Jing Xiao, Lin Yang, Le Lu
This is the goal of our work, where we develop a powerful system to harvest missing lesions from the DeepLesion dataset at high precision.
1 code implementation • 5 Sep 2020 • Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, YouBao Tang, Yuxing Tang, Lingyun Huang, Jing Xiao, Le Lu
For example, DeepLesion is such a large-scale CT image dataset with lesions of various types, but it also has many unlabeled lesions (missing annotations).
1 code implementation • 4 Dec 2020 • Ke Yan, Jinzheng Cai, Dakai Jin, Shun Miao, Dazhou Guo, Adam P. Harrison, YouBao Tang, Jing Xiao, JingJing Lu, Le Lu
We introduce such an approach, called Self-supervised Anatomical eMbedding (SAM).