Yunzhi Wang

According to our database, Yunzhi Wang authored at least 13 papers between 2016 and 2019.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2019

Developing a new quantitative imaging marker to predict pathological complete response to neoadjuvant chemotherapy.

Faranak Aghaei, Alan B. Hollingsworth, Seyedehnafiseh Mirniaharikandehei, Yunzhi Wang, Hong Liu, Bin Zheng

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Design, fabrication and evaluation of non-imaging, label-free pre-screening tool using quantified bio-electrical tissue profile.

Ali Zarafshani, Yunzhi Wang, Seyedeh-Nafiseh Mirniaharikandehei, Morteza Heidari, Faranak Aghaei, Siqi Wang, Liangzhong Xiang, Bin Zheng

Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019

2018

Applying a CAD-generated imaging marker to assess short-term breast cancer risk.

Seyedehnafiseh Mirniaharikandehei, Ali Zarafshani, Morteza Heidari, Yunzhi Wang, Faranak Aghaei, Bin Zheng

Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Association between mammogram density and background parenchymal enhancement of breast MRI.

Faranak Aghaei, Gopichandh Danala, Yunzhi Wang, Ali Zarafshani, Wei Qian, Hong Liu, Bin Zheng

Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2017

A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.

Yunzhi Wang, Yuchen Qiu, Theresa C. Thai, Kathleen N. Moore, Hong Liu, Bin Zheng

Comput. Methods Programs Biomed., 2017

Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.

Shiju Yan, Yunzhi Wang, Faranak Aghaei, Yuchen Qiu, Bin Zheng

Int. J. Comput. Assist. Radiol. Surg., 2017

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images.

Yunzhi Wang, Yuchen Qiu, Theresa C. Thai, Kathleen N. Moore, Hong Liu, Bin Zheng

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Apply radiomics approach for early stage prognostic evaluation of ovarian cancer patients: a preliminary study.

Gopichandh Danala, Yunzhi Wang, Theresa C. Thai, Camille Gunderson, Katherine Moxley, Kathleen N. Moore, Robert S. Mannel, Hong Liu, Bin Zheng, Yuchen Qiu

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2016

Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome.

Yunzhi Wang, Yuchen Qiu, Theresa C. Thai, Kathleen N. Moore, Hong Liu, Bin Zheng

BMC Medical Imaging, 2016

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients.

Yunzhi Wang, Yuchen Qiu, Theresa C. Thai, Kathleen N. Moore, Kai Ding, Hong Liu, Bin Zheng

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method.

Maxine Tan, Faranak Aghaei, Yunzhi Wang, Wei Qian, Bin Zheng

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology.

Yuchen Qiu, Yunzhi Wang, Shiju Yan, Maxine Tan, Samuel Cheng, Hong Liu, Bin Zheng

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Applying a radiomics approach to predict prognosis of lung cancer patients.

Nastaran Emaminejad, Shiju Yan, Yunzhi Wang, Wei Qian, Yubao Guan, Bin Zheng

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016