عنوان

Understanding and interpreting machine learning in medical image computing applications :

شابک

3030026280

شابک

9783030026288

شابک اشتباه

3030026272

شابک اشتباه

3030026299

شابک اشتباه

9783030026271

شابک اشتباه

9783030026271

شابک اشتباه

9783030026295

عنوان اصلي

Understanding and interpreting machine learning in medical image computing applications :

نام عام مواد

[Book]

ساير اطلاعات عنواني

first International Workshops, MLCN 2018, DLF 2018, and iMIMIC 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018 : proceedings /

نام نخستين پديدآور

Danail Stoyanov, Zeike Taylor, Seyed Mostafa Kia, Ipek Oguz, Mauricio Reyes 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 (xvi, 148 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

11038

متن يادداشت

International conference proceedings.

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

Intro -- Additional Workshop Editors -- MLCN 2018 Preface -- DLF 2018 Preface -- iMIMIC 2018 Preface -- Organization -- Contents -- First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018 -- Alzheimer's Disease Modelling and Staging Through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes -- 1 Introduction -- 2 Method -- 3 Results -- 3.1 Benchmark on Synthetic Data -- 3.2 Application on Real Data -- 4 Conclusion -- References

متن يادداشت

2.2 Deep Learning Framework -- 3 Experiments and Results -- 3.1 Datasets Description -- 3.2 Evaluation Metric -- 3.3 Implementation Detail -- 3.4 Feature Learning Experiments and Results -- 4 Conclusions -- References -- Evaluation of Strategies for PET Motion Correction -- Manifold Learning vs. Deep Learning -- 1 Introduction -- 2 Methods -- 2.1 Network Architecture -- 2.2 Training Details -- 3 Experiments -- 3.1 Synthetic Dataset -- 3.2 Comparison Method: Data-Driven Gating -- 3.3 Assessment of Corrected Volume Quality -- 4 Discussion and Conclusions -- References

متن يادداشت

3 Methods -- 3.1 Data -- 3.2 Model -- 3.3 Visualization Methods -- 4 Results -- 4.1 Classification -- 4.2 Relevant Brain Areas -- 4.3 Differences Between Visualization Methods -- 5 Conclusion -- References -- Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data -- 1 Introduction -- 1.1 Multi-site Data and Batch Effects -- 2 Machine Learning and Functional Connectivity Graphs -- 3 Batch Effects Correction Techniques -- 3.1 Adding Site as Covariate -- 3.2 Z-Score Normalization -- 3.3 Whitening -- 3.4 Solving Linear Transformations -- 4 Experiments and Results

متن يادداشت

4.1 Dataset -- 4.2 Experiments and Results -- 5 Discussion -- References -- First International Workshop on Deep Learning Fails Workshop, DLF 2018 -- Towards Robust CT-Ultrasound Registration Using Deep Learning Methods -- 1 Introduction -- 2 Methods -- 3 Data -- 3.1 Clinical Data -- 3.2 Training Data -- 4 Experiments -- 4.1 Mono-Modal -- 4.2 Multi-modal (Simulated) -- 4.3 Inaccurate Ground Truth -- 4.4 CT-US -- 5 Discussion and Conclusion -- References -- To Learn or Not to Learn Features for Deformable Registration? -- 1 Introduction -- 2 Method -- 2.1 Discrete Optimization

متن يادداشت

Multi-channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease -- 1 Introduction -- 2 Method -- 2.1 Multi-channel Variational Inference -- 2.2 Gaussian Linear Case -- 3 Experiments -- 3.1 Experiments on Linearly Generated Synthetic Datasets -- 3.2 Application to Clinical and Medical Imaging Data in AD -- 4 Discussion and Conclusion -- References -- Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer's Disease -- 1 Introduction -- 2 Related Work -- 2.1 Alzheimer Classification -- 2.2 Visualization Methods

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 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 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030026288

شماره استاندارد بين المللي کتاب و موسيقي

9783030026271

شماره استاندارد بين المللي کتاب و موسيقي

9783030026295

عنوان اصلي به زبان ديگر

DLF 2018

عنوان اصلي به زبان ديگر

IMIMIC 2018

عنوان اصلي به زبان ديگر

MLCN 2018

موضوع مستند نشده

Computer-assisted surgery, Congresses.

موضوع مستند نشده

Diagnostic imaging-- Data processing, Congresses.

موضوع مستند نشده

Image Interpretation, Computer-Assisted.

موضوع مستند نشده

Artificial intelligence.

موضوع مستند نشده

Computer-assisted surgery.

موضوع مستند نشده

Computers-- Computer Graphics.

موضوع مستند نشده

Computers-- Computer Science.

موضوع مستند نشده

Computers-- Intelligence (AI) & Semantics.

موضوع مستند نشده

Computers-- Programming-- Algorithms.

موضوع مستند نشده

Diagnostic imaging-- Data processing.

موضوع مستند نشده

Health & safety aspects of IT.

موضوع مستند نشده

Image processing.

موضوع مستند نشده

Life sciences: general issues.

موضوع مستند نشده

Mathematical theory of computation.

موضوع مستند نشده

Mathematics-- Logic.

موضوع مستند نشده

Medical-- General.

موضوع مستند نشده

COM012000

موضوع مستند نشده

UYQV

موضوع مستند نشده

UYT

موضوع مستند نشده

UYT

شماره

ويراست

شماره رده

نشانه اثر

شماره رده

مستند نام اشخاص تاييد نشده

Kia, Seyed Mostafa

مستند نام اشخاص تاييد نشده

Oguz, Ipek

مستند نام اشخاص تاييد نشده

Reyes, Mauricio

مستند نام اشخاص تاييد نشده

Stoyanov, Danail

مستند نام اشخاص تاييد نشده

Taylor, Zeike

مستند نام تنالگان تاييد نشده

MLCN (Workshop)(1st :2018 :, Granada, Spain)

مستند نام تنالگان تاييد نشده

DLF (Workshop)(1st :2018 :, Granada, Spain)

مستند نام تنالگان تاييد نشده

iMIMIC (Workshop)(1st :2018 :, Granada, Spain)

مستند نام تنالگان تاييد نشده

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

تاريخ عمليات

20200823074425.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y