Zeju Li|Konstantinos Kamnitsas|Ben Glocker - JoVE Visualize

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IEEE Transactions on Medical Imaging|December 22, 2020

Analyzing Overfitting Under Class Imbalance in Neural Networks for Image SegmentationZeju Li, Konstantinos Kamnitsas, Ben Glocker

IEEE Transactions on Medical Imaging|June 5, 2023

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in SegmentationZeju Li, Konstantinos Kamnitsas, Qi Dou, et al.

IEEE Transactions on Medical Imaging|April 6, 2023

Context Label Learning: Improving Background Class Representations in Semantic SegmentationZeju Li, Konstantinos Kamnitsas, Cheng Ouyang, et al.

IEEE Transactions on Medical Imaging|April 25, 2017

Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground TruthVanya V Valindria, Ioannis Lavdas, Wenjia Bai, et al.

Medical Physics|July 31, 2017

Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approachIoannis Lavdas, Ben Glocker, Konstantinos Kamnitsas, et al.

Medical Image Analysis|November 20, 2016

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentationKonstantinos Kamnitsas, Christian Ledig, Virginia F J Newcombe, et al.

Medical Image Analysis|February 21, 2019

Evaluating reinforcement learning agents for anatomical landmark detectionAmir Alansary, Ozan Oktay, Yuanwei Li, et al.

Plos One|March 29, 2017

Multi-channel MRI segmentation of eye structures and tumors using patient-specific featuresCarlos Ciller, Sandro De Zanet, Konstantinos Kamnitsas, et al.

The Lancet. Digital Health|December 17, 2020

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation studyMiguel Monteiro, Virginia F J Newcombe, Francois Mathieu, et al.

IEEE Transactions on Medical Imaging|September 30, 2017

Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and SegmentationOzan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, et al.

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Showing results (1-10 of 152) with videos related to

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IEEE Transactions on Medical Imaging|December 22, 2020

Analyzing Overfitting Under Class Imbalance in Neural Networks for Image SegmentationZeju Li, Konstantinos Kamnitsas, Ben Glocker

IEEE Transactions on Medical Imaging|June 5, 2023

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in SegmentationZeju Li, Konstantinos Kamnitsas, Qi Dou, et al.

IEEE Transactions on Medical Imaging|April 6, 2023

Context Label Learning: Improving Background Class Representations in Semantic SegmentationZeju Li, Konstantinos Kamnitsas, Cheng Ouyang, et al.

IEEE Transactions on Medical Imaging|April 25, 2017

Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground TruthVanya V Valindria, Ioannis Lavdas, Wenjia Bai, et al.

Medical Physics|July 31, 2017

Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approachIoannis Lavdas, Ben Glocker, Konstantinos Kamnitsas, et al.

Medical Image Analysis|November 20, 2016

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentationKonstantinos Kamnitsas, Christian Ledig, Virginia F J Newcombe, et al.

Medical Image Analysis|February 21, 2019

Evaluating reinforcement learning agents for anatomical landmark detectionAmir Alansary, Ozan Oktay, Yuanwei Li, et al.

Plos One|March 29, 2017

Multi-channel MRI segmentation of eye structures and tumors using patient-specific featuresCarlos Ciller, Sandro De Zanet, Konstantinos Kamnitsas, et al.

The Lancet. Digital Health|December 17, 2020

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation studyMiguel Monteiro, Virginia F J Newcombe, Francois Mathieu, et al.

IEEE Transactions on Medical Imaging|September 30, 2017

Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and SegmentationOzan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, et al.

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