Machine Learning in Medical Imaging - Lecture Notes in Computer Science
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Published By Springer International Publishing

9783030009182, 9783030009199

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Correction to: Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF)

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_47 ◽

2020 ◽

pp. C1-C1

Author(s):

Zhenghan Fang ◽

Yong Chen ◽

Mingxia Liu ◽

Yiqiang Zhan ◽

Weili Lin ◽

...

Keyword(s):

Deep Learning ◽

Magnetic Resonance ◽

Tissue Quantification ◽

Undersampled Data

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End-to-End Lung Nodule Detection in Computed Tomography

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_5 ◽

2018 ◽

pp. 37-45 ◽

Cited By ~ 3

Author(s):

Dufan Wu ◽

Kyungsang Kim ◽

Bin Dong ◽

Georges El Fakhri ◽

Quanzheng Li

Keyword(s):

Computed Tomography ◽

Lung Nodule ◽

Lung Nodule Detection ◽

Nodule Detection ◽

End To End

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Joint Registration And Segmentation Of Xray Images Using Generative Adversarial Networks

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_9 ◽

2018 ◽

pp. 73-80 ◽

Cited By ~ 12

Author(s):

Dwarikanath Mahapatra ◽

Zongyuan Ge ◽

Suman Sedai ◽

Rajib Chakravorty

Keyword(s):

Generative Adversarial Networks ◽

Adversarial Networks

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CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_6 ◽

2018 ◽

pp. 46-54 ◽

Cited By ~ 9

Author(s):

Youbao Tang ◽

Jinzheng Cai ◽

Le Lu ◽

Adam P. Harrison ◽

Ke Yan ◽

...

Keyword(s):

Image Enhancement ◽

Transfer Learning ◽

Generative Adversarial Networks ◽

Ct Image ◽

Lesion Segmentation ◽

Adversarial Networks

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Nuclei Detection Using Mixture Density Networks

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_28 ◽

2018 ◽

pp. 241-248 ◽

Cited By ~ 4

Author(s):

Navid Alemi Koohababni ◽

Mostafa Jahanifar ◽

Ali Gooya ◽

Nasir Rajpoot

Keyword(s):

Mixture Density ◽

Nuclei Detection

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Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-Ray Segmentation

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_17 ◽

2018 ◽

pp. 143-151 ◽

Cited By ~ 33

Author(s):

Cheng Chen ◽

Qi Dou ◽

Hao Chen ◽

Pheng-Ann Heng

Keyword(s):

Domain Adaptation ◽

X Ray ◽

Unsupervised Domain Adaptation ◽

Chest X Ray

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Adversarial Image Registration with Application for MR and TRUS Image Fusion

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_23 ◽

2018 ◽

pp. 197-204 ◽

Cited By ~ 11

Author(s):

Pingkun Yan ◽

Sheng Xu ◽

Ardeshir R. Rastinehad ◽

Brad J. Wood

Keyword(s):

Image Registration ◽

Image Fusion ◽

Trus Image

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Automatic Accurate Infant Cerebellar Tissue Segmentation with Densely Connected Convolutional Network

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_27 ◽

2018 ◽

pp. 233-240

Author(s):

Jiawei Chen ◽

Han Zhang ◽

Dong Nie ◽

Li Wang ◽

Gang Li ◽

...

Keyword(s):

Tissue Segmentation ◽

Convolutional Network ◽

Cerebellar Tissue

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Computation of Total Kidney Volume from CT Images in Autosomal Dominant Polycystic Kidney Disease Using Multi-task 3D Convolutional Neural Networks

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_44 ◽

2018 ◽

pp. 380-388 ◽

Cited By ~ 3

Author(s):

Deepak Keshwani ◽

Yoshiro Kitamura ◽

Yuanzhong Li

Keyword(s):

Neural Networks ◽

Kidney Disease ◽

Polycystic Kidney Disease ◽

Convolutional Neural Networks ◽

Autosomal Dominant ◽

Ct Images ◽

Kidney Volume ◽

Polycystic Kidney ◽

Total Kidney Volume ◽

Autosomal Dominant Polycystic Kidney

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Retinal Blood Vessel Segmentation Using a Fully Convolutional Network – Transfer Learning from Patch- to Image-Level

Machine Learning in Medical Imaging - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00919-9_20 ◽

2018 ◽

pp. 170-178 ◽

Cited By ~ 2

Author(s):

Taibou Birgui Sekou ◽

Moncef Hidane ◽

Julien Olivier ◽

Hubert Cardot

Keyword(s):

Blood Vessel ◽

Transfer Learning ◽

Vessel Segmentation ◽

Retinal Blood Vessel ◽

Convolutional Network ◽

Fully Convolutional Network ◽

Blood Vessel Segmentation

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Machine Learning in Medical Imaging - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Correction to: Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF)

End-to-End Lung Nodule Detection in Computed Tomography

Joint Registration And Segmentation Of Xray Images Using Generative Adversarial Networks

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Nuclei Detection Using Mixture Density Networks

Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-Ray Segmentation

Adversarial Image Registration with Application for MR and TRUS Image Fusion

Automatic Accurate Infant Cerebellar Tissue Segmentation with Densely Connected Convolutional Network

Computation of Total Kidney Volume from CT Images in Autosomal Dominant Polycystic Kidney Disease Using Multi-task 3D Convolutional Neural Networks

Retinal Blood Vessel Segmentation Using a Fully Convolutional Network – Transfer Learning from Patch- to Image-Level

Machine Learning in Medical Imaging - Lecture Notes in Computer Science
Latest Publications