Medical image computing and computer assisted intervention -- MICCAI 2019 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings. Part VI /
The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented w...
| Corporate Authors: | International Conference on Medical Image Computing and Computer-Assisted Intervention Shenzhen Shi, China) |
|---|---|
| Other Authors: | International Conference on Medical Image Computing and Computer-Assisted Intervention, Shen, Dinggang,, Liu, Tianming, Dr., Peters, Terry M., 1948 January 5-, Staib, Lawrence,, Essert, Caroline,, Zhou, Xiangyun Sean,, Yap, Pew-Thian,, Khan, Ali,, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
2019.
|
| Physical Description: |
1 online resource (xxxviii, 860 pages) : illustrations (some color). |
| Series: |
Lecture notes in computer science ;
11769. LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics. |
| Subjects: |
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| 111 | 2 | |a International Conference on Medical Image Computing and Computer-Assisted Intervention |n (22nd : |d 2019 : |c Shenzhen Shi, China) | |
| 245 | 1 | 0 | |a Medical image computing and computer assisted intervention -- MICCAI 2019 : |b 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings. |n Part VI / |c Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan (eds.). |
| 246 | 3 | |a MICCAI 2019. | |
| 264 | 1 | |a Cham, Switzerland : |b Springer, |c 2019. | |
| 300 | |a 1 online resource (xxxviii, 860 pages) : |b illustrations (some color). | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
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| 490 | 1 | |a Lecture notes in computer science ; |v 11769. | |
| 490 | 1 | |a LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics. | |
| 500 | |a International conference proceedings. | ||
| 500 | |a Includes author index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed October 15, 2019). | |
| 505 | 0 | |a Intro; Preface; Organization; Accepted MICCAI 2019 Papers; Awards Presented at MICCAI 2018, Granada, Spain; Contents -- Part VI; Computed Tomography; Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma; 1 Introduction; 2 The Segmentation-for-Classification Approach; 2.1 The Overall Framework; 2.2 Training: Multi-scale Deeply-Supervised Segmentation; 2.3 Testing: Coarse-to-Fine Segmentation with Post-processing; 3 Experiments; 3.1 Dataset and Settings; 3.2 Segmentation Results; 3.3 Classification Results; 4 Conclusion; References. | |
| 505 | 8 | |a MVP-Net: Multi-view FPN with Position-Aware Attention for Deep Universal Lesion Detection1 Introduction; 2 Methodology; 2.1 Multi-view FPN; 2.2 Attention Based Feature Aggregation; 2.3 Position-Aware Modeling; 3 Experiments; 3.1 Experimental Setup; 3.2 Comparison with State-of-the-Arts; 3.3 Ablation Study; 4 Conclusion; References; Spatial-Frequency Non-local Convolutional LSTM Network for pRCC Classification; 1 Introduction; 2 Methodology; 2.1 Overview; 2.2 Spatial-Frequency Non-local Convolutional LSTM Network Architecture; 3 Experiments and Results; 3.1 Dataset; 3.2 Pre-processing. | |
| 505 | 8 | |a 3.3 Implementation Details3.4 Results; 4 Conclusion; References; BCD-Net for Low-Dose CT Reconstruction: Acceleration, Convergence, and Generalization; 1 Introduction; 2 BCD-Net for Low-Dose CT Reconstruction; 2.1 Architecture; 2.2 Training BCD-Net; 2.3 Convergence Analysis; 2.4 Computational Complexity; 3 Experimental Results and Discussion; 3.1 Experimental Setup; 3.2 Results and Discussion; 4 Conclusions; References; Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning; 1 Introduction; 2 Methods; 2.1 Dataset; 2.2 Data Augmentation. | |
| 505 | 8 | |a 2.3 Value Loss and Cross Entropy Loss Function3 Experiments and Results; 3.1 Evaluation Metrics; 3.2 Semi-supervised Algorithm; 3.3 Double Loss Function Collaborative Training; 4 Conclusion and Discussion; References; Closing the Gap Between Deep and Conventional Image Registration Using Probabilistic Dense Displacement Networks; 1 Introduction and Related Work; 2 Methods; 3 Experimental Validation; 4 Results and Discussions; 5 Conclusion; References; Generating Pareto Optimal Dose Distributions for Radiation Therapy Treatment Planning; Abstract; 1 Introduction; 2 Methods. | |
| 505 | 8 | |a 2.1 Prostate Patient Data and Pareto Plan Generation2.2 Deep Learning Architecture; 2.3 Training and Evaluation; 3 Results; 4 Discussion and Conclusion; References; PAN: Projective Adversarial Network for Medical Image Segmentation; 1 Introduction; 2 Method; 2.1 Adversarial Training; 2.2 Segmentor (S); 2.3 Adversarial Networks; 3 Experiments and Results; 4 Conclusion; References; Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction; 1 Introduction; 2 Methodology; 3 Experimental Evaluations; 4 Conclusion; References. | |
| 520 | |a The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging. | ||
| 650 | 0 | |a Diagnostic imaging |x Data processing |v Congresses. | |
| 650 | 0 | |a Computer-assisted surgery |v Congresses. | |
| 650 | 6 | |a Imagerie pour le diagnostic |x Informatique |v Congrès. | |
| 650 | 6 | |a Chirurgie assistée par ordinateur |v Congrès. | |
| 650 | 7 | |a Computer-assisted surgery. |2 fast. | |
| 650 | 7 | |a Diagnostic imaging |x Data processing. |2 fast. | |
| 655 | 0 | |a Electronic books. | |
| 655 | 2 | |a Congress. | |
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| 655 | 7 | |a Conference papers and proceedings. |2 fast. | |
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| 655 | 7 | |a Actes de congrès. |2 rvmgf. | |
| 700 | 1 | |a Shen, Dinggang, |e editor. | |
| 700 | 1 | |a Liu, Tianming, |c Dr. |1 https://id.oclc.org/worldcat/entity/E39PCjFP7fhdT8QWXc94BT4QMd, |e editor. | |
| 700 | 1 | |a Peters, Terry M., |d 1948 January 5- |1 https://id.oclc.org/worldcat/entity/E39PBJwXdwBqJVQ8FcCwmdpByd, |e editor. | |
| 700 | 1 | |a Staib, Lawrence, |e editor. | |
| 700 | 1 | |a Essert, Caroline, |e editor. | |
| 700 | 1 | |a Zhou, Xiangyun Sean, |e editor. | |
| 700 | 1 | |a Yap, Pew-Thian, |e editor. | |
| 700 | 1 | |a Khan, Ali, |e editor. | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 830 | 0 | |a Lecture notes in computer science ; |v 11769. | |
| 830 | 0 | |a LNCS sublibrary. |n SL 6, |p Image processing, computer vision, pattern recognition, and graphics. | |
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