Kenny H. Cha

Orcid: 0000-0003-3847-7448

According to our database1, Kenny H. Cha authored at least 40 papers between 2014 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

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

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

Bladder cancer segmentation using U-Net-based deep-learning.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 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, 2022

Deciphering deep ensembles for lung nodule analysis.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 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, 2019

2D and 3D bladder segmentation using U-Net-based deep-learning.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 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, 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, 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, California, United States, 27 February, 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, California, United States, 27 February, 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, California, United States, 27 February, 2016

Automatic staging of bladder cancer on CT urography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

Automatic detection of ureter lesions in CT urography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 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, California, United States, 27 February, 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, California, United States, 27 February, 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, 2014

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


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