activity
20192022
most citedDeep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement

12 citations · 16 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV202212 cited

Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement

Xi Fang, Daeseung Kim, Xuanang Xu +8

Simulating facial appearance change following bony movement is a critical step in orthognathic surgical planning for patients with jaw deformities. Conventional biomechanics-based…

eess.IV2020

Integrative Analysis for COVID-19 Patient Outcome Prediction

Hanqing Chao, Xi Fang, Jiajin Zhang +13

While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome predictio…

cs.CV2020

Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction

Xi Fang, Pingkun Yan

Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-org…

eess.IV20194 cited

Unified Multi-scale Feature Abstraction for Medical Image Segmentation

Xi Fang, Bo Du, Sheng Xu +2

Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis. For example, locating and segmenting the…

physics.med-ph2019

A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing

Zhao Peng, Xi Fang, Pingkun Yan +7

Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing orga…