Machine Learning in Medical Imaging

Idioma: inglés

Editorial: Springer, Springer Okt 2023, 2023

3031456750 / 9783031456756

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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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This item is printed on demand - Print on Demand Titel. Neuware -GEMTrans: A General, Echocardiography-based, Multi-Level Transformer Framework for Cardiovascular Diagnosis.- Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder.- LMT: Longitudinal Mixing Training a Framework for the Prediction of Disease Progression Using a Single Image.- Identifying Alzheimer's Disease-induced Topology Alterations in Structural Networks using Convolutional Neural Networks.- Specificity-Aware Federated Graph Learning for Brain Disorder Analysis with Functional MRI.- 3D Transformer Based on Deformable Patch Location for Differential Diagnosis Between Alzheimer's Disease and Frontotemporal Dementia.- Consisaug: A Consistency-based Augmentation for Polyp Detection in Endoscopy Image Analysis.- Cross-view Contrastive Mutual Learning across Masked Autoencoders for Mammography Diagnosis.- Modeling Life-span Brain Age from Large-scale Dataset based on Multi-levelInformation Fusion.- Boundary-Constrained Graph Network for Tooth Segmentation on 3D Dental Surfaces.- FAST-Net: A Coarse-to-fine Pyramid Network for Face-Skull Transformation.- Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping.- Consistency Loss for Improved Colonoscopy Landmark Detection with Vision Transformers.- Radiomics Boosts Deep Learning Model for IPMN Classification.- Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection.- Enhancing Anomaly Detection in Melanoma Diagnosis through Self-Supervised Training and Lesion Comparison.- DynBrainGNN: Towards Spatio-Temporal Interpretable Graph Neural Network based on Dynamic Brain Connectome for Psychiatric Diagnosis.- Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs.- Towards Unified Modality Understanding for Alzheimer's Disease Diagnosis using Incomplete Multi-Modality Data.- COVID-19 Diagnosis Based on Swin Transformer Model with Demographic Information Fusion and Enhanced Multi-head Attention Mechanism.- MoViT: Memorizing Vision Transformers for Medical Image Analysis.- Fact-Checking of AI-Generated Reports.- Is Visual Explanation with Grad-CAM More Reliability for Deeper Neural Networks a Case Study with Automatic Pneumothorax Diagnosis.- Group Distributionally Robust Knowledge Distillation.- A Bone Lesion Identification Network (BLIN) in Whole Body CT Images.- Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment.- Data-driven Classification of Fatty Liver From 3D Unenhanced Abdominal CT Scans.- Replica-based Federated Learning with Heterogeneous Architectures for Graph Super-Resolution.- A Multitask Deep Learning Model for Voxel-level Brain Age Estimation.- Deep Nearest Neighbors for Anomaly Detectionin Chest X-Rays.- CCMix: Curriculum of Class-wise Mixup for Long-tailed Medical Image Classification.- MEDKD: Enhancing Medical Image Classification with Multiple Expert Decoupled Knowledge Distillation for Long-Tail Data.- Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation.- Non-Uniform Sampling-Based Breast Cancer Classification.- A Scaled Denoising Attention-based Transformer for Breast Cancer Detection and Classification.- Distilling Local Texture Features for Colorectal Tissue Classification in Low Data Regimes.- Delving into Ipsilateral Mammogram Assessment under Multi-View Network.- ARHNet: Adaptive Region Harmonization for Lesion-aware Augmentation to Improve Segmentation Performance.- Normative Aging for an Individual's Full BrSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 504 pp. Englisch.…

Título
Machine Learning in Medical Imaging
Autor
Xiaohuan Cao
Editorial
Springer, Springer Okt 2023
Año de publicación
2023
Estado
Neu
Encuadernación
Taschenbuch
Idioma
inglés
ISBN 10
3031456750
ISBN 13
9783031456756
Peso del artículo
756 gramos
Dimensiones
235x155x28 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Alemania

Vendedor de 5 estrellas

Vendedor de IberLibro desde 23 de enero de 2017

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Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

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