Machine Learning in Medical Imaging
Springer International Publishing (Verlag)
978-3-319-10580-2 (ISBN)
Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development.- Graph-Based Label Propagation in Fetal brain MR Images.- Deep Learning Based Automatic immune Cell Detection for Immunohistochemistry Images.- Stacked Multiscale Feature learning for Domain Independent Medical Image Segmentation.- Detection of Mammographic Masses by Content-Based Image Retrieval.- Inferring Sources of Dementia Progression with Network Diffusion Model.- 3D Intervertebral Disc Localization through Representation Learning with Knowledge Transfer.- Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification.- Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression.- Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease.- Gleason Grading of Prostate Tumors with Max-Margin Conditional Random Fields.- Learning Distance Transform for Boundary Detection and Deformable Segmentation in CT Prostate Images.- Geodesic Geometric mean of Regional Covariance Descriptors as an Image-Level Descriptor for nuclear Atypia Grading in Breast Images.- A constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation.- Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation.- Fetal Abdominal Standard Plane Localization through Representation Learning with Knowledge Transfer.- Searching for Structures of Interest in an Ultrasound Video Sequence.- Anatomically Constrained Weak Classifier Fusion for Early Detection of Alzheimer's Disease.- Automatic Bone and Marrow Extraction from Dual Energy CT through SVM Margin-Based Multi-Material Decomposition Model Selection.- Sparse Discriminative Feature Selection for Multi-Class Alzheimer's Disease Classification.- Context-aware Anatomical Landmark Detection: Application to Deformable Model Initialization in Prostate CT Images.-Optimal MAP Parameters Estimation in STAPLE-Learning from Performance Parameters versus Image Similarity Information.- Colon Biopsy Classification Using Crypt Architecture.- Network Guided Group Feature Selection for Classification of Autism Spectrum Disorder.- Deformation Field Correction for Spatial Normalization of PET Images Using a Population-derived Partial Least Squares Model.- Novel Multi-Atlas Segmentation by Matrix Completion.- Structured Random Forest for Myocardium Delineation in 3D Echocardiography.- Improved Reproducibility of Neuroanatomical Definition through Diffeomorphometry and Complexity Reduction.- Topological Descriptors of Histology Images.- Robust Deep Learning for Improved Classification of AD/MCI Patients.- Subject Specific Sparse Dictionary Learning for Atlas Based Brain MRI Segmentation.- Online Discriminative Multi-Atlas Learning with Application to Isointense Infant Brain Segmentation.
Erscheint lt. Verlag | 23.9.2014 |
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Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
Zusatzinfo | XII, 332 p. 136 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 174 g |
Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
Schlagworte | Bildgebende Verfahren (Medizin) • brain network analysis • cellular image analysis • computer-aided diagnostics/detection • Deep learning • Health Informatics • Image Registration • Image Retrieval • Image Segmentation • machine learning • manifold learning • Maschinelles Lernen • Medical Imaging • multi-modality fusion • multi-task learning • sparse learning • transfer learning • Unsupervised Learning |
ISBN-10 | 3-319-10580-9 / 3319105809 |
ISBN-13 | 978-3-319-10580-2 / 9783319105802 |
Zustand | Neuware |
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