Advances In Computational Techniques For Biomedical Image Analysis, Koundal, Deepika
Автор: K. Kamalanand, B. Thayumanavan, P. Mannar Jawahar Название: Computational Techniques for Dental Image Analysis ISBN: 1522562435 ISBN-13(EAN): 9781522562436 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 236010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: With the technology innovations dentistry has witnessed in all its branches over the past three decades, the need for more precise diagnostic tools and advanced imaging methods has become mandatory across the industry. Recent advancements to imaging systems are playing an important role in efficient diagnoses, treatments, and surgeries.Computational Techniques for Dental Image Analysis provides innovative insights into computerized methods for automated analysis. The research presented within this publication explores pattern recognition, oral pathologies, and diagnostic processing. It is designed for dentists, professionals, medical educators, medical imaging technicians, researchers, oral surgeons, and students, and covers topics centered on easier assessment of complex cranio-facial tissues and the accurate diagnosis of various lesions at early stages.
Автор: Joao Tavares; R. M. Natal Jorge Название: Advances in Computational Vision and Medical Image Processing ISBN: 904818066X ISBN-13(EAN): 9789048180660 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The present book contains extended versions of papers presented in the Conference VIPIMAGE 2007 - ECCOMAS Thematic Conference on Computational Vision and Medical Image. This ECCOMAS thematic conference was on computational vision and medical image processing.
Автор: Trucco, Emanuele Название: Computational Retinal Image Analysis ISBN: 0081028164 ISBN-13(EAN): 9780081028162 Издательство: Elsevier Science Рейтинг: Цена: 142610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence.
Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations (e.g. anatomical landmarks location, blood vessel segmentation), lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insight into current investigations drawing from artificial intelligence and big data (retinal biomarkers for risk of systemic conditions).
This comprehensive and structured one-stop reference is ideal for researchers and graduate students in retinal image analysis, researchers in computational ophthalmology from computer science, artificial intelligence, biomedical engineering, health informatics, ophthalmology, and precision medicine, as well as optometrists
A unique, well-structured and integrated overview of retinal image analysis
Gives insight into the future such as large-scale screening programs, precision medicine, computer-assisted personalized eye care
Includes plans and aspirations of companies and professional bodies
Автор: Chengjun Liu Название: Recent Advances in Intelligent Image Search and Video Retrieval ISBN: 331984816X ISBN-13(EAN): 9783319848167 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval.
Автор: Danail Stoyanov; Zeike Taylor; Francesco Ciompi; Y Название: Computational Pathology and Ophthalmic Medical Image Analysis ISBN: 3030009483 ISBN-13(EAN): 9783030009489 Издательство: Springer Рейтинг: Цена: 61480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 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 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis.
Автор: Dajiang Zhu; Jingwen Yan; Heng Huang; Li Shen; Pau Название: Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy ISBN: 303033225X ISBN-13(EAN): 9783030332259 Издательство: Springer Рейтинг: Цена: 54030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: MBIA.- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm.- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction.- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation.- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding.- Mapping the spatio-temporal functional coherence in the resting brain.- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA.- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains.- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder.- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data.- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study.- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network.- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes.- Structural Similarity based Anatomical and Functional Brain Imaging Fusion.- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution.- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank.- MFCA.- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models.- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm.- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development.- Surface Foliation Based Brain Morphometry Analysis.- Mixture Probabilistic Principal Geodesic Analysis.- A Geodesic Mixed Effects Model in Kendall's Shape Space.- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.
Автор: Changming Sun; Tomasz Bednarz; Tuan D. Pham; Pasca Название: Signal and Image Analysis for Biomedical and Life Sciences ISBN: 3319109839 ISBN-13(EAN): 9783319109831 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Part I Signal Analysis
1. Visual Analytics of Signalling Pathways Using Time Profiles; David K. G. Ma, Christian Stolte, Sandeep Kaur, Michael Bain and Se an I. O'Donoghue
2. Modeling of Testosterone Regulation by Pulse-modulated Feedback; Per Mattsson and Alexander Medvedev
3. Hybrid Algorithms for Multiple Change-Point Detection in Biological Sequence; Madawa Priyadarshana, Tatiana Polushina and Georgy Sofronov
4. Stochastic Anomaly Detection in Eye-Tracking Data for Quantification of Motor Symptoms in Parkinson's Disease; Daniel Jansson, Alexander Medvedev, Hans Axelson and Dag Nyholm
5. Identification of the Reichardt Elementary Motion Detector Model; Egi Hidayat, Alexander Medvedev and Karin Nordstrцm
6. Multi-Complexity Ensemble Measures for Gait Time Series Analysis: Application to Diagnostics, Monitoring and Biometrics; Valeriy Gavrishchaka, Olga Senyukova and Kristina Davis
7. Development of a Motion Capturing and Load Analyzing System for Caregivers Aiding a Patient to Sit Up in Bed; Akemi Nomura, Yasuko Ando, Tomohiro Yano, Yosuke Takami, Shoichiro Ito, Takako Sato, Akinobu Nemoto and Hiroshi Arisawa
8. Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-Scale K-means; Guohun Zhu, Yan Li, Peng (Paul) Wen and Shuaifang Wang
9. Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring; Humaira Nisar, Aamir Saeed Malik, Rafi Ullah, Seong-O Shim, Abdullah Bawakid, Muhammad Burhan Khan and Ahmad Rauf Subhani
Part II Image Analysis
10. Towards Automated Quantitative Vasculature Understanding via Ultra High-Resolution Imagery; Rongxin Li, Dadong Wang, Changming Sun, Ryan Lagerstrom, Hai Tan, You He and Tiqiao Xiao
11. Cloud Based Toolbox for Image Analysis, Processing and Reconstruction Tasks; Tomasz Bednarz, Dadong Wang, Yulia Arzhaeva, Ryan Lagerstrom, Pascal Vallotton, Neil Burdett, Alex Khassapov, Piotr Szul, Shiping Chen, Changming Sun, Luke Domanski, Darren Thompson, Timur Gureyev and John A. Taylor
12. Pollen Image Classification Using the Classifynder System: Algorithm Comparison and a Case Study on New Zealand Honey; Ryan Lagerstrom, Katherine Holt, Yulia Arzhaeva, Leanne Bischof, Simon Haberle, Felicitas Hopf and David Lovell
13. Digital Image Processing and Analysis for Activated Sludge Wastewater Treatment; Muhammad Burhan Khan, Xue Yong Lee, Humaira Nisar, Choon Aun Ng, Kim Ho Yeap and Aamir Saeed Malik
14. A Complete System for 3D Reconstruction of Roots for Phenotypic Analysis; Pankaj Kumar, Jinhai Cai and Stan Miklavcic
Автор: Changming Sun; Tomasz Bednarz; Tuan D. Pham; Pasca Название: Signal and Image Analysis for Biomedical and Life Sciences ISBN: 3319359029 ISBN-13(EAN): 9783319359021 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Part I Signal Analysis
1. Visual Analytics of Signalling Pathways Using Time Profiles; David K. G. Ma, Christian Stolte, Sandeep Kaur, Michael Bain and Se an I. O'Donoghue
2. Modeling of Testosterone Regulation by Pulse-modulated Feedback; Per Mattsson and Alexander Medvedev
3. Hybrid Algorithms for Multiple Change-Point Detection in Biological Sequence; Madawa Priyadarshana, Tatiana Polushina and Georgy Sofronov
4. Stochastic Anomaly Detection in Eye-Tracking Data for Quantification of Motor Symptoms in Parkinson's Disease; Daniel Jansson, Alexander Medvedev, Hans Axelson and Dag Nyholm
5. Identification of the Reichardt Elementary Motion Detector Model; Egi Hidayat, Alexander Medvedev and Karin Nordstrцm
6. Multi-Complexity Ensemble Measures for Gait Time Series Analysis: Application to Diagnostics, Monitoring and Biometrics; Valeriy Gavrishchaka, Olga Senyukova and Kristina Davis
7. Development of a Motion Capturing and Load Analyzing System for Caregivers Aiding a Patient to Sit Up in Bed; Akemi Nomura, Yasuko Ando, Tomohiro Yano, Yosuke Takami, Shoichiro Ito, Takako Sato, Akinobu Nemoto and Hiroshi Arisawa
8. Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-Scale K-means; Guohun Zhu, Yan Li, Peng (Paul) Wen and Shuaifang Wang
9. Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring; Humaira Nisar, Aamir Saeed Malik, Rafi Ullah, Seong-O Shim, Abdullah Bawakid, Muhammad Burhan Khan and Ahmad Rauf Subhani
Part II Image Analysis
10. Towards Automated Quantitative Vasculature Understanding via Ultra High-Resolution Imagery; Rongxin Li, Dadong Wang, Changming Sun, Ryan Lagerstrom, Hai Tan, You He and Tiqiao Xiao
11. Cloud Based Toolbox for Image Analysis, Processing and Reconstruction Tasks; Tomasz Bednarz, Dadong Wang, Yulia Arzhaeva, Ryan Lagerstrom, Pascal Vallotton, Neil Burdett, Alex Khassapov, Piotr Szul, Shiping Chen, Changming Sun, Luke Domanski, Darren Thompson, Timur Gureyev and John A. Taylor
12. Pollen Image Classification Using the Classifynder System: Algorithm Comparison and a Case Study on New Zealand Honey; Ryan Lagerstrom, Katherine Holt, Yulia Arzhaeva, Leanne Bischof, Simon Haberle, Felicitas Hopf and David Lovell
13. Digital Image Processing and Analysis for Activated Sludge Wastewater Treatment; Muhammad Burhan Khan, Xue Yong Lee, Humaira Nisar, Choon Aun Ng, Kim Ho Yeap and Aamir Saeed Malik
14. A Complete System for 3D Reconstruction of Roots for Phenotypic Analysis; Pankaj Kumar, Jinhai Cai and Stan Miklavcic
Автор: M. Emre Celebi, Teresa Mendonca, Jorge S. Marques Название: Dermoscopy Image Analysis ISBN: 1138892874 ISBN-13(EAN): 9781138892873 Издательство: Taylor&Francis Рейтинг: Цена: 47970.00 T Наличие на складе: Невозможна поставка. Описание: Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.
Автор: Jiri Jan Название: Medical Image Processing, Reconstruction and Analysis: Concepts and Methods, Second Edition ISBN: 113831028X ISBN-13(EAN): 9781138310285 Издательство: Taylor&Francis Рейтинг: Цена: 224570.00 T Наличие на складе: Невозможна поставка. Описание: Medical Image Processing, Reconstruction and Analysis – Concepts and Methods explains the general principles and methods of image processing, focusing namely on applications used in medical imaging – providing a theoretical yet clear and easy to follow explanation of underlying generic concepts. The content of this book is divided into three parts: Part I – Images as Multidimensional Signals provides the introduction tobasic image processing theory, explaining it for both analogue and digital image representations. Part II – Imaging Systems as Data Sources offers a non-traditional view on imaging modalities, explaining – without technical details – their basic principles influencing the properties of the obtained images, with emphasis placed on analyzing the internal signals and (pre)image data that are to be processed by the methods described in this book. Part III – Image Processing and Analysis focuses on such vital image processing topics as tomographic image reconstruction, image fusion, methods if image enhancement and restoration. It explains concepts of both fundamental-level image analysis detailing local feature, edge and texture analysis, image segmentation and morphological transforms, and higher-level analysis, as principal and independent component analysis and namely the new analysis area based on deep learning, namely that using convolutional neural networks. Briefly, also the medical image-processing environment is briefly treated, including the processes for image archiving and communication. Features Presents a good, theoretically exact yet understandable overview of basic theory related to image processing and analysis, with practical interpretations of all theoretical conclusions Provides a concise treatment of a wide variety of medical imaging modalities with respect to properties of image data to be processed Includes topical discussions on medical image reconstruction, fusion, enhancement and restoration as well as on image analysis including the recently appearing deep-learning based methods Explores appropriate applications relevant to particular chapters
Автор: Danail Stoyanov; Zeike Taylor; Enzo Ferrante; Adri Название: Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities ISBN: 3030006883 ISBN-13(EAN): 9783030006884 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed joint proceedings of the Second International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2018 and the First International Workshop on Integrating Medical Imaging and Non-Imaging Modalities, Beyond MIC 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 6 full papers presented at GRAIL 2018 and the 5 full papers presented at BeYond MIC 2018 were carefully reviewed and selected. The GRAIL papers cover a wide range of develop graph-based models for the analysis of biomedical images and encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. The Beyond MIC papers cover topics of novel methods with significant imaging and non-imaging components, addressing practical applications and new datasets
Автор: M. Jorge Cardoso; Tal Arbel; Enzo Ferrante; Xavier Название: Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics ISBN: 3319676741 ISBN-13(EAN): 9783319676746 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.
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