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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data [[electronic resource] ] : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data [[electronic resource] ] : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XVII, 254 p. 113 illus., 79 illus. in color.)
Disciplina 616.07540285
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Health informatics
Image Processing and Computer Vision
Artificial Intelligence
Health Informatics
ISBN 3-030-33391-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto DART 2019 -- Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation -- Temporal Consistency Objectives Regularize the Learning of Disentangled Representations -- Multi-layer Domain Adaptation for Deep Convolutional Networks -- Intramodality Domain Adaptation using Self Ensembling and Adversarial Training -- Learning Interpretable Disentangled Representations using Adversarial VAEs -- Synthesising Images and Labels Between MR Sequence Types With CycleGAN -- Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning -- Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans -- A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection -- Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images -- Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases -- Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions -- MIL3ID 2019 -- Self-supervised learning of inverse problem solvers in medical imaging -- Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation -- A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images -- CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT -- Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images -- Semi-supervised Learning of Fetal Anatomy from Ultrasound -- Multi-modal segmentation with missing MR sequences using pre-trained fusion networks -- More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation -- Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition -- A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation -- Transfer Learning from Partial Annotations for Whole Brain Segmentation -- Learning to Segment Skin Lesions from Noisy Annotations -- A Weakly Supervised Method for Instance Segmentation of Biological Cells -- Towards Practical Unsupervised Anomaly Detection on Retinal Images -- Fine tuning U-Net for ultrasound image segmentation: which layers -- Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance.
Record Nr. UNISA-996466435303316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XVII, 254 p. 113 illus., 79 illus. in color.)
Disciplina 616.07540285
616.0754
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Health informatics
Image Processing and Computer Vision
Artificial Intelligence
Health Informatics
ISBN 3-030-33391-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto DART 2019 -- Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation -- Temporal Consistency Objectives Regularize the Learning of Disentangled Representations -- Multi-layer Domain Adaptation for Deep Convolutional Networks -- Intramodality Domain Adaptation using Self Ensembling and Adversarial Training -- Learning Interpretable Disentangled Representations using Adversarial VAEs -- Synthesising Images and Labels Between MR Sequence Types With CycleGAN -- Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning -- Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans -- A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection -- Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images -- Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases -- Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions -- MIL3ID 2019 -- Self-supervised learning of inverse problem solvers in medical imaging -- Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation -- A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images -- CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT -- Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images -- Semi-supervised Learning of Fetal Anatomy from Ultrasound -- Multi-modal segmentation with missing MR sequences using pre-trained fusion networks -- More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation -- Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition -- A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation -- Transfer Learning from Partial Annotations for Whole Brain Segmentation -- Learning to Segment Skin Lesions from Noisy Annotations -- A Weakly Supervised Method for Instance Segmentation of Biological Cells -- Towards Practical Unsupervised Anomaly Detection on Retinal Images -- Fine tuning U-Net for ultrasound image segmentation: which layers -- Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance.
Record Nr. UNINA-9910349274803321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neurosurgery Case Review: Questions and Answers / / by: Nader, Remi, Sabbagh, Abdulrahman J., Elbabaa, Samer K., Al-Jehani, Hosam, Gasco, Jaime, Gragnaniello, Cristian, Abou-Al-Shaar, Hussam
Neurosurgery Case Review: Questions and Answers / / by: Nader, Remi, Sabbagh, Abdulrahman J., Elbabaa, Samer K., Al-Jehani, Hosam, Gasco, Jaime, Gragnaniello, Cristian, Abou-Al-Shaar, Hussam
Autore Abdelmoity Ahmed T
Edizione [Second edition.]
Pubbl/distr/stampa New York, New York : , : Thieme, , [2020]
Descrizione fisica 1 online resource (648 pages)
Disciplina 617.480076
Soggetto topico Nervous system - Surgery
Soggetto genere / forma Examination Questions
Case Reports
ISBN 1-63853-388-1
1-62623-199-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910793925903321
Abdelmoity Ahmed T  
New York, New York : , : Thieme, , [2020]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neurosurgery Case Review: Questions and Answers / / by: Nader, Remi, Sabbagh, Abdulrahman J., Elbabaa, Samer K., Al-Jehani, Hosam, Gasco, Jaime, Gragnaniello, Cristian, Abou-Al-Shaar, Hussam
Neurosurgery Case Review: Questions and Answers / / by: Nader, Remi, Sabbagh, Abdulrahman J., Elbabaa, Samer K., Al-Jehani, Hosam, Gasco, Jaime, Gragnaniello, Cristian, Abou-Al-Shaar, Hussam
Autore Abdelmoity Ahmed T
Edizione [Second edition.]
Pubbl/distr/stampa New York, New York : , : Thieme, , [2020]
Descrizione fisica 1 online resource (648 pages)
Disciplina 617.480076
Soggetto topico Nervous system - Surgery
Soggetto genere / forma Examination Questions
Case Reports
ISBN 1-63853-388-1
1-62623-199-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910807615303321
Abdelmoity Ahmed T  
New York, New York : , : Thieme, , [2020]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Total Knee Arthroplasty [[electronic resource] ] : A Review of Medical and Biomedical Engineering and Science Concepts / / by Emre Tokgoz, Sarah Levitt, Diana Sosa, Nicholas A. Carola, Vishal Patel
Total Knee Arthroplasty [[electronic resource] ] : A Review of Medical and Biomedical Engineering and Science Concepts / / by Emre Tokgoz, Sarah Levitt, Diana Sosa, Nicholas A. Carola, Vishal Patel
Autore Tokgoz Emre
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (272 pages)
Disciplina 617.5820592
Altri autori (Persone) LevittSarah
SosaDiana
CarolaNicholas A
PatelVishal
Soggetto topico Biomedical engineering
Biomechanics
Orthopedic surgery
Robotics
Biomedical Engineering and Bioengineering
Surgical Orthopedics
Robotic Engineering
ISBN 3-031-31100-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Surgical Approaches Used for Total Knee Arthroplasty -- Pre-existing Conditions Leading to Total Knee Arthroplasty -- Surgical Approach Comparison in Total Knee Arthroplasty -- Perioperative Patient Care for Total Knee Arthroplasty -- Complications of Total Knee Arthroplasty -- Ergonomics of Total Knee Arthroplasty -- Medical Improvement Suggestions for Total Knee Arthroplasty -- Biomechanics of Total Knee Arthroplasty -- Robotics Applications in Total Knee Arthroplasty -- Impact of Manufacturing on Total Knee Arthroplasty -- Optimization Investigations on Total Knee Arthroplasty -- Artificial Intelligence, Deep Learning, and Machine Learning Applications in Total Knee Arthroplasty -- Advancing Engineering of Total Knee Arthroplasty.
Record Nr. UNINA-9910734833503321
Tokgoz Emre  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui