Kenny H. Cha

Orcid: 0000-0003-3847-7448

According to our database1, Kenny H. Cha authored at least 42 papers between 2014 and 2025.

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

Timeline

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PhD thesis 
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Online presence:

On csauthors.net:

Bibliography

2025
Bias Amplification to Facilitate the Systematic Evaluation of Bias Mitigation Methods.
IEEE J. Biomed. Health Informatics, February, 2025

2023
Weakly supervised deep learning for predicting the response to hormonal treatment of women with atypical endometrial hyperplasia: a feasibility study.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023

Survival prediction for patients with metastatic urothelial cancer after immunotherapy using machine learning.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Bladder cancer treatment response assessment in CT urography by using deep-learning and radiomics.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Bladder cancer segmentation using U-Net-based deep-learning.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Software as a Medical Device (SaMD) at the FDA: Regulatory Science and Review.
Proceedings of the IEEE John Vincent Atanasoff International Symposium on Modern Computing, 2023

AFE-GAN: Synthesizing Electrocardiograms with Atrial Fibrillation Characteristics Using Generative Adversarial Networks.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

2022
Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters.
BMC Bioinform., 2022

Effect of computerized decision support on diagnostic accuracy and intra-observer variability in multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

Deciphering deep ensembles for lung nodule analysis.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

2021
Multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography with and without computerized decision support.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Assessment of bone fragility in projection images using radiomic features.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2020
Supplementing training with data from a shifted distribution for machine learning classifiers: adding more cases may not always help.
Proceedings of the Medical Imaging 2020: Image Perception, 2020

Mammographic Image Conversion Between Source and Target Acquisition Systems Using cGAN.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets.
IEEE Trans. Medical Imaging, 2019

Deep learning based bladder cancer treatment response assessment.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2D and 3D bladder segmentation using U-Net-based deep-learning.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support system.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2018
Compression of deep convolutional neural network for computer-aided diagnosis of masses in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Generalization error analysis: deep convolutional neural network in mammography.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Bladder cancer treatment response assessment with radiomic, clinical and radiologist semantic features.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Bladder cancer staging in CT urography: effect of stage labels on statistical modeling of a decision support system.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Bladder cancer treatment response assessment in CT urography using two-channel deep-learning network.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Computer-aided detection of bladder wall thickening in CT urography (CTU).
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2017
Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Segmentation of inner and outer bladder wall using deep-learning convolutional neural network in CT urography.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Bladder cancer treatment response assessment using deep learning in CT with transfer learning.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Computer-aided detection of bladder masses in CT urography (CTU).
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2016
Reference state estimation of breast computed tomography for registration with digital mammography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Deep-learning convolution neural network for computer-aided detection of microcalcifications in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

First and second-order features for detection of masses in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Automatic staging of bladder cancer on CT urography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Automatic detection of ureter lesions in CT urography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Computer-aided detection of bladder mass within non-contrast-enhanced region of CT Urography (CTU).
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

2015
Ureter segmentation in CT urography (CTU) by COMPASS with multiscale Hessian enhancement.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Computer-aided detection of bladder mass within contrast-enhanced region of CTU.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

2014
Segmentation of urinary bladder in CT urography (CTU) using CLASS with enhanced contour conjoint procedure.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014

Comparison of CLASS and ITK-SNAP in segmentation of urinary bladder in CT urography.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014


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