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Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis: First International Workshop, SUSI 2019, and 4th International Workshop, PIPPI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings 2019 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 190 pages, height x width: 235x155 mm, weight: 454 g, 68 Illustrations, color; 29 Illustrations, black and white; XVII, 190 p. 97 illus., 68 illus. in color., 1 Paperback / softback
  • Sērija : Image Processing, Computer Vision, Pattern Recognition, and Graphics 11798
  • Izdošanas datums: 13-Oct-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030328740
  • ISBN-13: 9783030328740
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Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis: First International Workshop, SUSI 2019, and 4th International Workshop, PIPPI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings 2019 ed.Palielināt
  • Formāts: Paperback / softback, 190 pages, height x width: 235x155 mm, weight: 454 g, 68 Illustrations, color; 29 Illustrations, black and white; XVII, 190 p. 97 illus., 68 illus. in color., 1 Paperback / softback
  • Sērija : Image Processing, Computer Vision, Pattern Recognition, and Graphics 11798
  • Izdošanas datums: 13-Oct-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030328740
  • ISBN-13: 9783030328740
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030328740.html
Keywords:
This book constitutes the refereed joint proceedings of the First International Workshop on Smart Ultrasound Imaging, SUSI 2019, and the 4th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019.The 10 full papers presented at SUSI 2019 and the 10 full papers presented at PIPPI 2019 were carefully reviewed and selected.





The SUSI papers cover a wide range of medical applications of B-Mode ultrasound, including cardiac (echocardiography), abdominal (liver), fetal, musculoskeletal, and lung.





The PIPPI papers cover the detailed scientific study of volumetric growth, myelination and cortical microstructure, placental structure and function.
First Workshop on Smart UltraSound Imaging.- Straight to the point:
reinforcement learning for user guidance in ultrasound.- Registration of
Untracked 2D Laparoscopic Ultrasound Liver Images to CT using Content-based
Retrieval and Kinematic Priors.- Direct Detection and Measurement of Nuchal
Translucency with Neural Networks from Ultrasound Images.- Automated left
ventricle dimension measurement in 2D cardiac ultrasound via an anatomically
meaningful CNN approach.- SPRNet: Automatic Fetal Standard Plane Recognition
Network for Ultrasound Images.- Representation Disentanglement for Multi-task
Learning with application to Fetal Ultrasound.- Adversarial Learning for
Deformable Image Registration: Application to 3D Ultrasound Image Fusion.-
Monitoring Achilles tendon healing progress in ultrasound imaging with
convolutional neural networks.- Deep Learning-based Pneumothorax Detection in
Ultrasound Videos.- Deep Learning Based Minimum Variance Beamforming for
Ultrasound Imaging.- 4th Workshop on Perinatal, Preterm and Paediatric Image
Analysis.- Estimation of preterm birth markers with U-Net segmentation
network.- Investigating Image Registration Impact on Preterm Birth
Classification: An Interpretable Deep Learning Approach.- Dual Network
Generative Adversarial Networks for Pediatric Echocardiography Segmentation.-
Reproducibility of Functional Connectivity Estimates in Motion Corrected
Fetal fMRI.- Plug-and-Play Priors for Reconstruction-based Placental Image
Registration.- A Longitudinal Study of the Evolution of the Central Sulcus
Shape in Preterm Infants using Manifold Learning.- Prediction of failure of
induction of labor (IOL) from ultrasound images using radioman features.-
Longitudinal analysis of fetal MRI in patients with prenatal spina bifida
repair.- Quantifying Residual Motion Artifacts in Fetal fMRI Data.-
Topology-preserving augmentation for CNN-based segmentation of congenital
heart defects from 3D paediatric CMR.