
Medical Content-Based Retrieval for Clinical Decision Support
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions

Content
- Title Page
- Preface
- Organization
- Table of Contents
- Workshop Overview
- Overview of the Second Workshop on Medical Content-Based Retrieval for Clinical Decision Support
- Introduction
- Highlights of the Presentations
- Main Novelties Presented
- Computer-Aided Diagnosis
- Visual Data Management
- Conclusions
- References
- Invited Speech
- Content-Based Retrieval in Endomicroscopy: Toward an Efficient {\it Smart Atlas} for Clinical Diagnosis
- Introduction
- Adjusting Bag of Visual Words for pCLE Retrieval
- Evaluating pCLE Retrieval Performance
- Estimating the Interpretation Difficulty
- Learning pCLE Semantic and Similarity Distance
- Conclusion
- References
- Medical Image Retrieval with Textual Approaches
- Biomedical Image Retrieval Using Multimodal Context and Concept Feature Spaces
- Introduction
- Image Feature Representation
- Context-Based Image Representation
- Concepts-Based Image Representation
- Multimodal Image Search
- Modality Detection and Filtering
- Experiments and Results
- Training for SVM
- Performance Analysis
- Conclusions
- References
- Using MeSH to Expand Queries in Medical Image Retrieval
- Introduction
- Related Work
- Collection Description
- Query Expansion Using MeSH
- Cross-Referencing Based Techniques
- Techniques Based in Entry Terms
- Results and Discussion
- Conclusions and Future Work
- References
- Building Implicit Dictionaries Based on Extreme Random Clustering for Modality Recognition
- Introduction
- Related Work
- Proposed Method
- Visual Feature Space
- Extreme Random Subspace Projection Ferns
- From Multiple Independent Partitions to an Implicit Dictionary
- Experiments and Results
- Discussion and Conclusion
- References
- Visual Word Based Approaches
- Superpixel-Based Interest Points for Effective Bags of Visual Words Medical Image Retrieval
- Introduction
- Related Work
- Methods
- Bags of Visual Words
- Interest Points: DoG, DENSE, Superpixel Points
- Distribution of Interest Points in the Image
- Experiments
- Results
- Conclusion
- References
- Using Multiscale Visual Words for Lung Texture Classification and Retrieval
- Introduction
- Methods
- Database
- Techniques Applied
- Results
- Discussion
- Conclusions and Future Work
- References
- Applications
- Histology Image Indexing Using a Non-negative Semantic Embedding
- Introduction
- Related Work
- Histology Images
- Matrix Factorization for Multimodal Indexing
- Non-negative Matrix Factorization
- Multimodal Indexing via NMF
- Non-negative Semantic Embedding
- Image Indexing and Search
- Experiments and Results
- Experimental Setup
- Experiments
- Conclusions
- References
- A Discriminative Distance Learning-BasedCBIR Framework for Characterization of Indeterminate Liver Lesions
- Introduction
- Related Work
- Method
- Intrinsic RF Similarity
- Online RF
- Low-Level Liver Lesion Descriptors
- High-Level Concepts
- Framework Application to Similar Hepatic Lesion Retrieval
- Empirical Study
- Conclusion and Future Work
- References
- Computer-Aided Diagnosis of Pigmented Skin Dermoscopic Images
- Introduction
- Computerized Diagnosis of Dermoscopic Images: State of the Art
- Database
- Classification of Dermoscopic Images: Proposed Approach
- Segmentation
- Feature Extraction
- Classification
- Results
- Conclusions and Future Work
- References
- Multidimensional Retrieval
- Texture Bags: Anomaly Retrieval in Medical Images Based on Local 3D-Texture Similarity
- Introduction
- Method
- Learning a Texture Vocabulary
- Retrieval
- Ranking of the Image Set
- Data
- Experiments
- Set-Up and Evaluation
- Results
- Conclusion
- References
- Evaluation of Fast 2D and 3D Medical Image Retrieval Approaches Based on Image Miniatures
- Introduction
- Descriptor Formation in Medical Image Retrieval
- Related Work
- Methods
- Image Miniatures as Descriptors
- Image Query.
- 3D Volume Retrieval.
- Distribution Fields (DFs)
- Histograms of Gradients (HOGs)
- Experiments
- ImageCLEF Data Set
- CT Data Set
- Results and Discussion
- ImageCLEF Data Set
- CT Data Set
- Conclusion and Outlook
- References
- Semantic Analysis of 3D Anatomical Medical Images for Sub-image Retrieval
- Introduction
- Proposed Approach
- Coarse Semantic Localization
- Organ Detection
- Inverted File Generation
- Experimental Results
- Conclusion
- References
- Author Index
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.