谭山｜华中科技大学｜学者主页

2026

Benchmarking large multimodal models for structured illumination microscopy quality assessment

F M Li, Shan Tan

International Conference on Optoelectronic Information and Optical Engineering (OIOE)

DOI

2026

Physics-guided learning of inverse reconstruction for structured illumination microscopy

Jiahao Liu, Shan Tan

DOI

2025

Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification

Tao Liu, Jiahao Liu, Dong Li, Shan Tan

Nature Communications

DOI

2025

Bio-friendly and high-precision super-resolution imaging through self-supervised reconstruction structured illumination microscopy

Jiahao Liu, Xue Dong, Huaide Lu, Tao Liu, Wei Liu, Xinyao Hu, Quan Meng, Amin Jiang, Tao Jiang, Xiao-Han Geng, Haosen Liu, Jun Cheng, E. Lam, Yan-Jun Liu, Shan Tan, Dong Li

Nature Methods

DOI

2025

Image Restoration Learning via Noisy Supervision in the Fourier Domain

Haosen Liu, Jiahao Liu, Shan Tan, Edmund Y. Lam

arXiv.org

DOI

2025

A CT metal artifact reduction method driven by implicit neural representation and dual-domain regularization

X. Liu, Yutong He, Yaoqin Xie, Shan Tan, Xiaokun Liang

SPIE Medical Imaging: Physics of Medical Imaging

DOI

2024

Deep Filtered Back Projection for CT Reconstruction

Xi Tan, Xuan Liu, Kaijia Xiang, Jing Wang, Shan Tan

IEEE Access

DOI

2024

Enhancing structural illumination microscopy with hybrid CNN-transformer and dynamic frequency loss

Tao Liu, Jingwei Niu, Jiahao Liu, Dong Li, Shan Tan

Optics and lasers in engineering

DOI

2024

Deep Learning Models for Discrimination of Parkinson's disease and Multiple System Atrophy on Brain Magnetic Resonance Imaging

Yuji Du, Xuanyan Wu, Hao Yang, Dong Liang, Jianing Jin, Dong-Ning Su, Chengzhang He, Yun Ling, Zhonglue Chen, Kang Ren, Tao Feng, Shan Tan

FAIML

DOI

2024

Transfer CLIP for Generalizable Image Denoising

Junting Cheng, Dong Liang, Shan Tan

Computer Vision and Pattern Recognition

DOI

2024

Exploring and Exploiting Multi-Modality Uncertainty for Tumor Segmentation on PET/CT

Susu Kang, Yixiong Kang, Shan Tan

IEEE journal of biomedical and health informatics

DOI

2023

Spectral Bayesian Uncertainty for Image Super-Resolution

Tao Liu, Junting Cheng, Shan Tan

Computer Vision and Pattern Recognition

DOI

2023

Diffusion probabilistic priors for zero‐shot low‐dose CT image denoising

X. Liu, Yao-Qin Xie, Chen-Bin Liu, Junting Cheng, Songhui Diao, Shan Tan, Xiaokun Liang

Medical Physics (Lancaster)

DOI

2023

Self-supervised denoising for structured illumination microscopy enables long-term super-resolution live-cell imaging

Xing-Ye Chen, C. Qiao, Tao Jiang, Jiahao Liu, Quan Meng, Yunmin, Zeng, Hao-Yu Chen, Yuan-Long Zhang, Xin-Yang Li, Guo-Xun Zhang, Yixin Li, Hui, Qiao, Jia-Min Wu, Shan Tan, Dong Li, Qiong-Hai Dai

2023

Learning feature fusion via an interpretation method for tumor segmentation on PET/CT

Susu Kang, Zhiyuan Chen, Laquan Li, Wei Lu, X. Qi, Shan Tan

Applied Soft Computing

DOI

2023

Image Denoising via Style Disentanglement

Jingwei Niu, Junting Cheng, Shan Tan

arXiv.org

DOI

2023

Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising

Junting Cheng, Tao Liu, Shan Tan

IEEE International Conference on Computer Vision

DOI

2023

Improving Reconstruction of Structured Illumination Microscopy Images via Dual-Domain Learning

Tao Liu, Jiahao Liu, Dong Li, Shan Tan

IEEE Journal of Selected Topics in Quantum Electronics

DOI

2023

Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains

X. Liu, Yao-Qin Xie, Songhui Diao, Shan Tan, Xiaokun Liang

IEEE Transactions on Medical Imaging

DOI

2022

Learning low-dose CT degradation from unpaired data with flow-based model.

Xuan Liu, Xiaokun Liang, L. Deng, Shan Tan, Yao-Qin Xie

Medical Physics (Lancaster)

DOI

2022

Group Sparsity Mixture Model and Its Application on Image Denoising

Haosen Liu, Laquan Li, Jiang-Bo Lu, Shan Tan

IEEE Transactions on Image Processing

DOI

2022

Decoupled Frequency Learning for Dynamic Scene Deblurring

Tao Liu, Shan Tan

International Conference on Pattern Recognition

DOI

2022

Bridging Feature Gaps to Improve Multi-Organ Segmentation on Abdominal Magnetic Resonance Image

Susu Kang, Mu-Yuan Yang, X. Qi, Jun Jiang, Shan Tan

IEEE journal of biomedical and health informatics

DOI

2020

Deep learning-enhanced fluorescence microscopy via degeneration decoupling.

Jiahao Liu, Xiaoshuai Huang, Liang-Yi Chen, Shan Tan

Optics Express

DOI

2020

Multi-to-binary network (MTBNet) for automated multi-organ segmentation on multi-sequence abdominal MRI images

Xiang-Ming Zhao, Minxin Huang, Laquan Li, X. Qi, Shan Tan

Physics in Medicine and Biology

DOI

2019

A protocol for structured illumination microscopy with minimal reconstruction artifacts

Junchao Fan, Xiaoshuai Huang, Liu-Ju Li, Shan Tan, Liang-Yi Chen

Biophysics Reports

DOI

2019

Deep Learning for Variational Multimodality Tumor Segmentation in PET/CT

Laquan Li, Xiang-Ming Zhao, Wei Lu, Shan Tan

Neurocomputing

DOI

2019

Structure tensor total variation for CBCT reconstruction

Xiaoling Tan, Kaijia Xiang, Liang Liu, Jing Wang, Shan Tan

Journal of X-Ray Science and Technology

DOI

2019

One-step deconvolution for multi-angle TIRF microscopy with enhanced resolution.

Junchao Fan, Xiaoshuai Huang, Liu-Ju Li, Liang-Yi Chen, Shan Tan

Biomedical Optics Express

DOI

2019

Variational PET/CT Tumor Co-segmentation Integrated with PET Restoration

Laquan Li, Wei Lu, Yihua Tan, Shan Tan

IEEE Transactions on Radiation and Plasma Medical Sciences

DOI

2019

Image Regularizations Based on the Sparsity of Corner Points

Haosen Liu, Shan Tan

IEEE Transactions on Image Processing

DOI

2019

Prediction of Anal Cancer Recurrence After Chemoradiotherapy Using Quantitative Image Features Extracted From Serial 18F-FDG PET/CT

Jiahui Wang, H. Zhang, M. Chuong, K. Latifi, Shan Tan, Wookjin Choi, S. Hoffe, R. Shridhar, Wei Lu

Frontiers in Oncology

DOI

2018

髋臼上螺钉通道的影像解剖学研究及其固定C1型骨盆骨折生物力学的有限元分析

谭山

《重庆医科大学》

2018

髋臼上区域置钉安全范围的影像学研究

谭山，高仕长，张安维，陈剑飞

《中国临床解剖学杂志》

2018

经皮骶髂关节螺钉固定变异骶骨的影像学初步研究

谭山，高仕长，张安维

《重庆医科大学学报》

2018

活细胞超灵敏结构光超高分辨率显微镜

黄小帅，李柳菊，范俊超，刘彦梅，谭山，陈良怡

《中国科学基金》

2018

Statistical Iterative CBCT Reconstruction Based on Neural Network

Binbin Chen, Kaijia Xiang, Z. Gong, Jing Wang, Shan Tan

IEEE Transactions on Medical Imaging

DOI

2018

Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy

Xiaoshuai Huang, Junchao Fan, Liu-Ju Li, Haosen Liu, Run-Long Wu, Yi Wu, Lisi Wei, Heng Mao, A. Lal, P. Xi, Li-Qiang Tang, Yunfeng Zhang, Yanmei Liu, Shan Tan, Liang-Yi Chen

Nature Biotechnology

DOI

2018

Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response

S. Riyahi, Wookjin Choi, Chia-Ju Liu, S. Nadeem, Shan Tan, H. Zhong, Wen-Gen Chen, A. Wu, J. Mechalakos, J. Deasy, Wei Lu

DATRA/PIPPI@MICCAI

DOI

2018

Tumor Co-Segmentation in PET/CT using Multi-Modality Fully Convolutional Neural Network

Xiang-Ming Zhao, Laquan Li, Wei Lu, Shan Tan

Physics in Medicine and Biology

DOI

2018

Fast, long-term super-resolution imaging with Hessian structured illumination microscopy

Liangyi Chen, Xiaoshuai Huang, Junchao Fan, Liuju Li, Shan Tan

Biomedical Imaging and Sensing Conference (BISC)

DOI

2017

S2横形螺钉固定变异骶骨Ⅲ区骨折的影像解剖学研究

张安维，高仕长，谭山，阳明明，鲁超

《中国临床解剖学杂志》

2017

The first MICCAI challenge on PET tumor segmentation

M. Hatt, Baptiste Laurent, A. Ouahabi, H. Fayad, Shan Tan, Laquan Li, Wei Lu, V. Jaouen, C. Tauber, Jakub Czakon, Filip Drapejkowski, W. Dyrka, S. Camarasu-Pop, F. Cervenansky, P. Girard, T. Glatard, Michael Kain, Yao Yao, C. Barillot, A. Kirov, D. Visvikis

Medical Image Anal.

DOI

2017

Low-dose CBCT Reconstruction Using Hessian Schatten Penalties

Liang Liu, Xinxin Li, Kaijia Xiang, Jing Wang, Shan Tan

IEEE Transactions on Medical Imaging

DOI

2017

Adaptive Region-Growing with Maximum Curvature Strategy for Tumor Segmentation in 18F-FDG PET

Shan Tan, Laquan Li, Wookjin Choi, M. Kang, W. D'Souza, Wei Lu

Physics in Medicine and Biology

DOI

2016

Radiomics for Survival Analysis and Prediction in Glioblastoma (GBM)—A Preliminary Study

H. Zhang, J. Molitoris, Shan Tan, I. Giacomelli, D. Scartoni, C. Gzell, N. Bhooshan, Wookjin Choi, Wei Lu, W. D'Souza, M. Mehta

DOI

2016

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties.

Q. Shi, Nanbo Sun, T. Sun, Jing Wang, Shan Tan

Biomedical Optics Express

DOI

2016

MO-FG-CAMPUS-IeP2-04: Multiple Penalties with Different Orders for Structure Adaptive CBCT Reconstruction.

Q. Shi, P. Cheng, Jing Wang, Shan Tan

Medical Physics (Lancaster)

DOI

2016

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

Laquan Li, Jian Wang, Wei Lu, Shan Tan

Computer Vision and Image Understanding

DOI

2016

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method.

Liu-Ju Li, Wen-Ju Lu, Shan Tan

Medical Physics (Lancaster)

DOI

2015

Optimal tumor segmentation in PET using multiple thresholds

Shan Tan, Laquan Li, Warren D. D'Souza, Wei Lu

Journal of Nuclear Medicine

2015

Analytics for Progression Free Survival and Distant Metastasis Prediction of Anal Cancer Patients After Chemoradiation Therapy Using Spatial Temporal FDG-PET/CT Features

M. Chuong, H. Zhang, Jian Z. Wang, K. Latifi, N. Saeed, Shan Tan, Wookjin Choi, S. Hoffe, R. Shridhar, Wei Lu

DOI

2015

Simultaneous PET image restoration and tumor segmentation using a generalized linear model: A global optimal solution

Laquan Li, Shuai Li, Wei Lu, Shan Tan

Journal of Nuclear Medicine

2015

SU‐E‐J‐270: Repeated 18F‐FDG PET/CTs Based Feature Analysis for the Predication of Anal Cancer Recurrence

Jian Z. Wang, M. Chuong, K. Latifi, N. Saeed, Shan Tan, Wookjin Choi, S. Hoffe, R. Shridhar, E. Moros, Wen-Ju Lu

DOI

2015

SU‐E‐J‐254: Evaluating the Role of Mid‐Treatment and Post‐Treatment FDG‐PET/CT in Predicting Progression‐Free Survival and Distant Metastasis of Anal Cancer Patients Treated with Chemoradiotherapy

H. Zhang, Jian Z. Wang, M. Chuong, W. D'Souza, K. Latifi, N. Saeed, Shan Tan, Wookjin Choi, S. Hoffe, R. Shridhar, E. Moros, Wen-Ju Lu

DOI

2015

CBCT reconstruction via a penalty combining total variation and its higher-degree term

Nanbo Sun, T. Sun, Jing Wang, Shan Tan

Medical Imaging

DOI

2015

TU‐CD‐BRA‐12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

L. Li, Wen-Ju Lu, Shan Tan

DOI

2015

Tumor segmentation in PET for multiple patients: one by one or all in one?

Shuai Li, Laquan Li, Xin Li, Wei Lu, Shan Tan

Journal of Nuclear Medicine

2015

Hessian Schatten-norm regularization for CBCT image reconstruction using fast iterative shrinkage-thresholding algorithm

Xinxin Li, Jiang Wang, Shan Tan

Medical Imaging

DOI

2015

Iterative CBCT reconstruction using Hessian penalty

T. Sun, Nanbo Sun, Jing Wang, Shan Tan

Physics in Medicine and Biology

DOI

2014

Multi-modality adaptive region-growing for tumor segmentation in 18F-FDG PET/CT

Shan Tan, Wen-Gen Chen, Hua Li, W. D'Souza, Wei Lu

2014

Quantitative 18F-FDG PET/CT image features for the evaluation of tumor response

Wei-Yu Lu, Shan Tan, H. Zhang, Wen-Gen Chen, S. Kligerman, M. Suntharalingam, W. D'Souza

2014

Radiobiological Modeling Based on 18F-Fluorodeoxyglucose Positron Emission Tomography Data for Esophageal Cancer

M. Guerrero, Shan Tan, Wei Lu

Journal of Nuclear Medicine & Radiation Therapy

DOI

2014

SU-D-12A-05: Iterative Reconstruction Techniques to Enable Intrinsic Respiratory Gated CT in Mice.

T. Sun, Y. Liu, Nanbo Sun, N. Mistry, Shan Tan

Medical Physics (Lancaster)

DOI

2014

The Predictive Value of Pretreatment 18-F-FDG-PET-CT in Locally Advanced Nasopharyngeal Cancer Patients Treated Definitively with Induction Chemotherapy Followed by Concurrent Chemo-Radiotherapy

M. Guerrero, Shan Tan, Wei Lu

2014

SU-F-18C-14: Hessian-Based Norm Penalty for Weighted Least-Square CBCT Reconstruction.

T. Sun, Nanbo Sun, Jing Wang, Shan Tan

Medical Physics (Lancaster)

DOI

2014

TU-C-12A-09: Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemo-Radiotherapy Using Quantitative PET/CT Features, Clinical Parameters and Demographics.

H. Zhang, Shan Tan, Wen-Gen Chen, S. Kligerman, Grace J. Kim, W. D. D'Souza, M. Suntharalingam, Wen-Jun Lu

Medical Physics (Lancaster)

DOI

2013

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns.

Shan Tan, H. Zhang, Yongxue Zhang, Wen-Gen Chen, W. D'Souza, Wei Lu

Medical Physics (Lancaster)

DOI

2013

TH-C-WAB-05: Blind Functional Volume Segmentation in PET.

Shan Tan, Wen-Ju Lu

Medical Physics (Lancaster)

DOI

2013

SU‐E‐J‐115: A Comparison of Methods for Functional Volume Delineation in PET: Simple Vs. Advanced Ones

Jing-Yin Wang, Liu-Ju Li, Wen-Ju Lu, Shan Tan

DOI

2013

Modeling Pathologic Response of Esophageal Cancer to Chemoradiotherapy Using Spatial-Temporal 18F-FDG PET Features, Clinical Parameters, and Demographics

H. Zhang, Shan Tan, Wen-Gen Chen, S. Kligerman, Grace J. Kim, W. D'Souza, M. Suntharalingam, Wei Lu

International Journal of Radiation Oncology, Biology, Physics

DOI

2013

SU‐E‐J‐106: The Correct Formula to Calculate Volume Overlap

Wen-Ju Lu, Shan Tan

DOI

2012

WE‐A‐217A‐06: Can Pre‐Chemoradiotherapy FDG PET/CT Identify Residual Metabolically Active Areas Within Individual Esophageal Tumors?

W. Lu, Shan Tan, S. Kligerman, Wen-Gen Chen, S. Feigenberg, H. Zhang, M. Suntharalingam, W. D'Souza

DOI

2012

Spatial-Temporal FDG-PET Features for Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemoradiotherapy

Shan Tan, S. Kligerman, Wen-Gen Chen, Minh Lu, Grace J. Kim, S. Feigenberg, W. D'Souza, M. Suntharalingam, Wei Lu

International Journal of Radiation Oncology, Biology, Physics

DOI

2012

Pre-Chemoradiation Therapy FDG PET/CT Cannot Identify Residual Metabolically Active Areas in Patients With Locally Advanced Esophageal Cancer

W. Lu, Shan Tan, Grace J. Kim, S. Feigenberg, H. Zhang, S. Kligerman, Wen-Gen Chen, W. D'Souza, M. Suntharalingam

DOI

2012

WE‐C‐BRA‐01: Best in Physics (Joint Imaging‐Therapy) ‐ Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemoradiotherapy Using Spatial‐Temporal FDG‐PET Features, Clinical Parameters and Demographics

H. Zhang, Shan Tan, Wen-Gen Chen, S. Kligerman, Grace J. Kim, W. D'Souza, M. Suntharalingam, Wei Lu

DOI

2012

Radiobiological Modeling Based on FDG-PET Data for Esophageal Cancer

M. Guerrero, Shan Tan, Wei Lu

DOI

2011

SU‐D‐BRC‐03: Spatial‐Temporal PET‐CT Features for Predicting Pathological Response of Esophagus Cancer to Chemo‐Radiation Therapies

Shan Tan, Wen-Gen Chen, Minh Lu, Grace J. Kim, S. Feigenberg, W. D'Souza, M. Suntharalingam, Wei Lu

DOI

2011

Spatial-Temporal 18F FDG-PET/CT Features Have Higher Discriminant Power than SUVmax and SUVpeak in Prediction of Pathological Response of Esophagus Tumor to Chemo-Radiation Therapies

Shan Tan, Grace J. Kim, S. Feigenberg, Wen-Gen Chen, Minh Lu, W. D'Souza, M. Suntharalingam, W. Lu

DOI

精选作品

期刊论文

Benchmarking large multimodal models for structured illumination microscopy quality assessment

Physics-guided learning of inverse reconstruction for structured illumination microscopy

Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification

Bio-friendly and high-precision super-resolution imaging through self-supervised reconstruction structured illumination microscopy

Image Restoration Learning via Noisy Supervision in the Fourier Domain

A CT metal artifact reduction method driven by implicit neural representation and dual-domain regularization

Deep Filtered Back Projection for CT Reconstruction

Enhancing structural illumination microscopy with hybrid CNN-transformer and dynamic frequency loss

Deep Learning Models for Discrimination of Parkinson's disease and Multiple System Atrophy on Brain Magnetic Resonance Imaging

Transfer CLIP for Generalizable Image Denoising

Exploring and Exploiting Multi-Modality Uncertainty for Tumor Segmentation on PET/CT

Spectral Bayesian Uncertainty for Image Super-Resolution

Diffusion probabilistic priors for zero‐shot low‐dose CT image denoising

Self-supervised denoising for structured illumination microscopy enables long-term super-resolution live-cell imaging

Learning feature fusion via an interpretation method for tumor segmentation on PET/CT

Image Denoising via Style Disentanglement

Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising

Improving Reconstruction of Structured Illumination Microscopy Images via Dual-Domain Learning

Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains

Learning low-dose CT degradation from unpaired data with flow-based model.

Group Sparsity Mixture Model and Its Application on Image Denoising

Decoupled Frequency Learning for Dynamic Scene Deblurring

Bridging Feature Gaps to Improve Multi-Organ Segmentation on Abdominal Magnetic Resonance Image

Deep learning-enhanced fluorescence microscopy via degeneration decoupling.

Multi-to-binary network (MTBNet) for automated multi-organ segmentation on multi-sequence abdominal MRI images

A protocol for structured illumination microscopy with minimal reconstruction artifacts

Deep Learning for Variational Multimodality Tumor Segmentation in PET/CT

Structure tensor total variation for CBCT reconstruction

One-step deconvolution for multi-angle TIRF microscopy with enhanced resolution.

Variational PET/CT Tumor Co-segmentation Integrated with PET Restoration

Image Regularizations Based on the Sparsity of Corner Points

Prediction of Anal Cancer Recurrence After Chemoradiotherapy Using Quantitative Image Features Extracted From Serial 18F-FDG PET/CT

髋臼上螺钉通道的影像解剖学研究及其固定C1型骨盆骨折生物力学的有限元分析

髋臼上区域置钉安全范围的影像学研究

经皮骶髂关节螺钉固定变异骶骨的影像学初步研究

活细胞超灵敏结构光超高分辨率显微镜

Statistical Iterative CBCT Reconstruction Based on Neural Network

Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy

Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response

Tumor Co-Segmentation in PET/CT using Multi-Modality Fully Convolutional Neural Network

Fast, long-term super-resolution imaging with Hessian structured illumination microscopy

S2横形螺钉固定变异骶骨Ⅲ区骨折的影像解剖学研究

The first MICCAI challenge on PET tumor segmentation

Low-dose CBCT Reconstruction Using Hessian Schatten Penalties

Adaptive Region-Growing with Maximum Curvature Strategy for Tumor Segmentation in 18F-FDG PET

Radiomics for Survival Analysis and Prediction in Glioblastoma (GBM)—A Preliminary Study

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties.

MO-FG-CAMPUS-IeP2-04: Multiple Penalties with Different Orders for Structure Adaptive CBCT Reconstruction.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method.

Optimal tumor segmentation in PET using multiple thresholds

Analytics for Progression Free Survival and Distant Metastasis Prediction of Anal Cancer Patients After Chemoradiation Therapy Using Spatial Temporal FDG-PET/CT Features

Simultaneous PET image restoration and tumor segmentation using a generalized linear model: A global optimal solution

SU‐E‐J‐270: Repeated 18F‐FDG PET/CTs Based Feature Analysis for the Predication of Anal Cancer Recurrence

SU‐E‐J‐254: Evaluating the Role of Mid‐Treatment and Post‐Treatment FDG‐PET/CT in Predicting Progression‐Free Survival and Distant Metastasis of Anal Cancer Patients Treated with Chemoradiotherapy

CBCT reconstruction via a penalty combining total variation and its higher-degree term

TU‐CD‐BRA‐12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

Tumor segmentation in PET for multiple patients: one by one or all in one?

Hessian Schatten-norm regularization for CBCT image reconstruction using fast iterative shrinkage-thresholding algorithm

Iterative CBCT reconstruction using Hessian penalty

Multi-modality adaptive region-growing for tumor segmentation in 18F-FDG PET/CT

Quantitative 18F-FDG PET/CT image features for the evaluation of tumor response

Radiobiological Modeling Based on 18F-Fluorodeoxyglucose Positron Emission Tomography Data for Esophageal Cancer

SU-D-12A-05: Iterative Reconstruction Techniques to Enable Intrinsic Respiratory Gated CT in Mice.

The Predictive Value of Pretreatment 18-F-FDG-PET-CT in Locally Advanced Nasopharyngeal Cancer Patients Treated Definitively with Induction Chemotherapy Followed by Concurrent Chemo-Radiotherapy

SU-F-18C-14: Hessian-Based Norm Penalty for Weighted Least-Square CBCT Reconstruction.

TU-C-12A-09: Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemo-Radiotherapy Using Quantitative PET/CT Features, Clinical Parameters and Demographics.

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns.

TH-C-WAB-05: Blind Functional Volume Segmentation in PET.

SU‐E‐J‐115: A Comparison of Methods for Functional Volume Delineation in PET: Simple Vs. Advanced Ones

Modeling Pathologic Response of Esophageal Cancer to Chemoradiotherapy Using Spatial-Temporal 18F-FDG PET Features, Clinical Parameters, and Demographics

SU‐E‐J‐106: The Correct Formula to Calculate Volume Overlap

WE‐A‐217A‐06: Can Pre‐Chemoradiotherapy FDG PET/CT Identify Residual Metabolically Active Areas Within Individual Esophageal Tumors?

Spatial-Temporal FDG-PET Features for Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemoradiotherapy

Pre-Chemoradiation Therapy FDG PET/CT Cannot Identify Residual Metabolically Active Areas in Patients With Locally Advanced Esophageal Cancer

WE‐C‐BRA‐01: Best in Physics (Joint Imaging‐Therapy) ‐ Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemoradiotherapy Using Spatial‐Temporal FDG‐PET Features, Clinical Parameters and Demographics

Radiobiological Modeling Based on FDG-PET Data for Esophageal Cancer

SU‐D‐BRC‐03: Spatial‐Temporal PET‐CT Features for Predicting Pathological Response of Esophagus Cancer to Chemo‐Radiation Therapies