Theresa C. Thai

According to our database1, Theresa C. Thai authored at least 14 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Developing a Novel Image Marker to Predict the Responses of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer Patients.
CoRR, 2023

2022
Recent advances and clinical applications of deep learning in medical image analysis.
Medical Image Anal., 2022

Virtual Adversarial Training for Semi-supervised Breast Mass Classification.
CoRR, 2022

2021
Recent advances and clinical applications of deep learning in medical image analysis.
CoRR, 2021

2020
Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients.
Comput. Methods Programs Biomed., 2020

2018
A performance comparison of low- and high-level features learned by deep convolutional neural networks in epithelium and stroma classification.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018

2017
A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.
Comput. Methods Programs Biomed., 2017

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images.
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.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2016
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration.
IEEE Trans. Medical Imaging, 2016

Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome.
BMC Medical Imaging, 2016

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

A B-spline image registration based CAD scheme to evaluate drug treatment response of ovarian cancer patients.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

2015
Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015


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