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Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Auto-Encoders
Wei Xiong, Neil Yeung, Shubo Wang +3
Objective and Impact Statement. We adopt a deep learning model for bone osteolysis prediction on computed tomography (CT) images of murine breast cancer bone metastases. Given the…
Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
Heliang Zheng, Huan Yang, Jianlong Fu +2
An important scenario for image quality assessment (IQA) is to evaluate image restoration (IR) algorithms. The state-of-the-art approaches adopt a full-reference paradigm that comp…
XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors
Cheng Peng, Haofu Liao, Gina Wong +3
A radiograph visualizes the internal anatomy of a patient through the use of X-ray, which projects 3D information onto a 2D plane. Hence, radiograph analysis naturally requires phy…
Unsupervised Low-light Image Enhancement with Decoupled Networks
Wei Xiong, Ding Liu, Xiaohui Shen +2
In this paper, we tackle the problem of enhancing real-world low-light images with significant noise in an unsupervised fashion. Conventional unsupervised learning-based approaches…
Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification
Wei Zhu, Haofu Liao, Wenbin Li +2
Skin disease classification from images is crucial to dermatological diagnosis. However, identifying skin lesions involves a variety of aspects in terms of size, color, shape, and…
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Haofu Liao, Wei-An Lin, S. Kevin Zhou +1
Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training…
Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment
Jianbo Yuan, Haofu Liao, Rui Luo +1
Generating radiology reports is time-consuming and requires extensive expertise in practice. Therefore, reliable automatic radiology report generation is highly desired to alleviat…
Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
Haofu Liao, Wei-An Lin, Zhimin Huo +4
A conventional approach to computed tomography (CT) or cone beam CT (CBCT) metal artifact reduction is to replace the X-ray projection data within the metal trace with synthesized…
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction
Wei-An Lin, Haofu Liao, Cheng Peng +5
Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are c…