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Zeynettin Akkus

Showing results (1-10 of 40) with videos related to

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Radiographics : a Review Publication of the Radiological Society of North America, Inc|February 18, 2017
Machine Learning for Medical ImagingBradley J Erickson, Panagiotis Korfiatis, Zeynettin Akkus, et al.
Journal of Digital Imaging|March 19, 2017
Toolkits and Libraries for Deep LearningBradley J Erickson, Panagiotis Korfiatis, Zeynettin Akkus, et al.
Pathology|March 1, 2021
Machine learning and augmented human intelligence use in histomorphology for haematolymphoid disordersAhmad Nanaa, Zeynettin Akkus, Winston Y Lee, et al.
Journal of Digital Imaging|June 4, 2017
Deep Learning for Brain MRI Segmentation: State of the Art and Future DirectionsZeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, et al.
Sensors (Basel, Switzerland)|July 31, 2020
Fully Automated Segmentation of Bladder Sac and Measurement of Detrusor Wall Thickness from Transabdominal Ultrasound ImagesZeynettin Akkus, Bae Hyung Kim, Rohit Nayak, et al.
Journal of Digital Imaging|September 20, 2017
Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRIYoungoh Bae, Kunaraj Kumarasamy, Issa M Ali, et al.
Ultrasound in Medicine & Biology|August 12, 2022
Deep Learning Estimation of Median Nerve Volume Using Ultrasound Imaging in a Human Cadaver ModelTomoyuki Kuroiwa, Jaidip Jagtap, Julia Starlinger, et al.
Ultrasound in Medicine & Biology|July 19, 2016
Fully Automated and Robust Tracking of Transient Waves in Structured Anatomies Using Dynamic ProgrammingZeynettin Akkus, Mahdi Bayat, Mathew Cheong, et al.
Journal of the American College of Radiology : JACR|February 4, 2018
Deep Learning in Radiology: Does One Size Fit All?Bradley J Erickson, Panagiotis Korfiatis, Timothy L Kline, et al.
Journal of Electrocardiology|March 9, 2020
Artificial intelligence for detecting mitral regurgitation using electrocardiographyJoon-Myoung Kwon, Kyung-Hee Kim, Zeynettin Akkus, et al.
Pageof 4

Showing results (1-10 of 40) with videos related to

Sort By:
Pageof 4
Radiographics : a Review Publication of the Radiological Society of North America, Inc|February 18, 2017
Machine Learning for Medical ImagingBradley J Erickson, Panagiotis Korfiatis, Zeynettin Akkus, et al.
Journal of Digital Imaging|March 19, 2017
Toolkits and Libraries for Deep LearningBradley J Erickson, Panagiotis Korfiatis, Zeynettin Akkus, et al.
Pathology|March 1, 2021
Machine learning and augmented human intelligence use in histomorphology for haematolymphoid disordersAhmad Nanaa, Zeynettin Akkus, Winston Y Lee, et al.
Journal of Digital Imaging|June 4, 2017
Deep Learning for Brain MRI Segmentation: State of the Art and Future DirectionsZeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, et al.
Sensors (Basel, Switzerland)|July 31, 2020
Fully Automated Segmentation of Bladder Sac and Measurement of Detrusor Wall Thickness from Transabdominal Ultrasound ImagesZeynettin Akkus, Bae Hyung Kim, Rohit Nayak, et al.
Journal of Digital Imaging|September 20, 2017
Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRIYoungoh Bae, Kunaraj Kumarasamy, Issa M Ali, et al.
Ultrasound in Medicine & Biology|August 12, 2022
Deep Learning Estimation of Median Nerve Volume Using Ultrasound Imaging in a Human Cadaver ModelTomoyuki Kuroiwa, Jaidip Jagtap, Julia Starlinger, et al.
Ultrasound in Medicine & Biology|July 19, 2016
Fully Automated and Robust Tracking of Transient Waves in Structured Anatomies Using Dynamic ProgrammingZeynettin Akkus, Mahdi Bayat, Mathew Cheong, et al.
Journal of the American College of Radiology : JACR|February 4, 2018
Deep Learning in Radiology: Does One Size Fit All?Bradley J Erickson, Panagiotis Korfiatis, Timothy L Kline, et al.
Journal of Electrocardiology|March 9, 2020
Artificial intelligence for detecting mitral regurgitation using electrocardiographyJoon-Myoung Kwon, Kyung-Hee Kim, Zeynettin Akkus, et al.
Pageof 4