عنوان

Deep learning in medical image analysis and Multimodal learning for clinical decision support :

شابک

3030008894

شابک

3030008908

شابک

9783030008895

شابک

9783030008901

شابک اشتباه

3030008886

شابک اشتباه

9783030008888

عنوان اصلي

Deep learning in medical image analysis and Multimodal learning for clinical decision support :

نام عام مواد

[Book]

ساير اطلاعات عنواني

4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings /

نام نخستين پديدآور

Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer Syeda-Mahmood et al. (eds.).

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

2018.

نام خاص و کميت اثر

1 online resource (xxvi, 387 pages) :

ساير جزييات

illustrations.

عنوان فروست

Lecture notes in computer science ;

عنوان فروست

LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics

مشخصه جلد

11045

متن يادداشت

Includes author index.

متن يادداشت

International conference proceedings.

متن يادداشت

Semi-Automated Extraction of Crohns Disease MR Imaging Markers using a 3D Residual CNN with Distance Prior -- Weakly Supervised Localisation for Fetal Ultrasound Images -- Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images -- Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks -- Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease -- Contextual Additive Networks to Efficiently Boost 3D Image Segmentations -- Longitudinal detection of radiological abnormalities with time-modulated LSTM -- SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays -- Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy -- Rapid Training Data Generation for Tissue Segmentation Using Global Approximate Block-Matching with Self-Organizing Maps -- Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images -- Deep semi-supervised segmentation with weight-averaged consistency targets -- Focal Dice Loss and Image Dilation for Brain Tumor Segmentation -- Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography -- Unsupervised feature learning for outlier detection with stacked convolutional autoencoders, siamese networks and Wasserstein autoencoders: application to epilepsy detection -- Automatic myocardial strain imaging in echocardiography using deep learning -- 3D Convolutional Neural Networks for Classification of Functional Connectomes -- Computed Tomography Image Enhancement using 3D Convolutional Neural Network -- Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning -- A Unified Framework Integrating Recurrent Fully-convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data -- Learning Optimal Deep Projection of 18 F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes -- Learning to Segment Medical Images with Scribble-Supervision Alone -- Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration -- TreeNet: Multi-Loss Deep Learning Network to Predict Branch Direction for Extracting 3D Anatomical Trees -- Active Deep Learning with Fisher Information for Patch-wise Semantic Segmentation -- UOLO -- automatic object detection and segmentation in biomedical images -- Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks -- Multi-Scale Residual Network with Two Channels of Raw CT Image and Its Differential Excitation Component for Emphysema Classification -- Nonlinear adaptively learned optimization for object localization in 3D medical images -- Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network -- UNet++: A Nested U-Net Architecture for Medical Image Segmentation -- MTMR-Net: Multi-Task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis -- PIMMS: Permutation Invariant Multi-Modal Segmentation -- Handling Missing Annotations for Semantic Segmentation with Deep ConvNets -- 3D Deep Affine-Invariant Shape Learning for Brain MR Image Segmentation -- ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans -- Unpaired Deep Cross-modality Synthesis with Fast Training -- Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification -- Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN -- A Multi-Scale Multiple Sclerosis Lesion Change Detection in a Multi-Sequence MRI -- Multi-task Sparse Low-rank Learning for Multi-classification of Parkinson's Disease -- Optic Disc segmentation in Retinal Fundus Images using Fully Convolutional Network and Removal of False-positives Based on Shape Features -- Integrating deformable modeling with 3D deep neural network segmentation.

بدون عنوان

0

متن يادداشت

This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030008895

شماره استاندارد بين المللي کتاب و موسيقي

9783030008888

شماره استاندارد بين المللي کتاب و موسيقي

9783030008901

عنوان اصلي به زبان ديگر

DLMIA 2018

عنوان اصلي به زبان ديگر

ML-CDS 2018

موضوع مستند نشده

Artificial intelligence-- Medical applications, Congresses.

موضوع مستند نشده

Medical informatics, Congresses.

موضوع مستند نشده

Artificial Intelligence.

موضوع مستند نشده

Computer Appl. in Social and Behavioral Sciences.

موضوع مستند نشده

Computers and Education.

موضوع مستند نشده

Health Informatics.

موضوع مستند نشده

Systems and Data Security.

موضوع مستند نشده

Artificial intelligence-- Medical applications.

موضوع مستند نشده

Computers-- Computer Graphics.

موضوع مستند نشده

Image processing.

موضوع مستند نشده

Medical informatics.

موضوع مستند نشده

COM012000

موضوع مستند نشده

UYQV

موضوع مستند نشده

UYT

موضوع مستند نشده

UYT

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Carneiro, Gustavo

مستند نام اشخاص تاييد نشده

Stoyanov, Danail

مستند نام اشخاص تاييد نشده

Syeda-Mahmood, Tanveer

مستند نام اشخاص تاييد نشده

Taylor, Zeike

مستند نام تنالگان تاييد نشده

DLMIA (Workshop)(4th :2018 :, Granada, Spain)

مستند نام تنالگان تاييد نشده

International Conference on Medical Image Computing and Computer-Assisted Intervention(21st :2018 :, Granada, Spain)

مستند نام تنالگان تاييد نشده

ML-CDS (Workshop)(8th :2018 :, Granada, Spain)

تاريخ عمليات

20200823072327.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y