Medical Image Understanding and Analysis
Springer International Publishing (Verlag)
978-3-031-48592-3 (ISBN)
Segmentation of White Matter Hyperintensities and Ischaemic Stroke Lesions in Structural MRI.- A Deep Learning Based Approach to Semantic Segmentation of Lung Tumour Areas in Gross Pathology Images.- Iterative Refinement Algorithm for Liver Segmentation Ground-Truth Generation using Fine-Tuning Weak Labels for CT and Structural MRI.- M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis Tasks.- BliMSR: Blind degradation modelling for generating high-resolution medical images.- Efficient Semantic Segmentation of Nuclei in Histopathology Images Using Segformer.- Cross-Modality Deep Transfer Learning: Application to Liver Segmentation in CT and MRI.- Can SegFormer be a True Competitor to U-Net for Medical Image Segmentation.- Harnessing the Potential of Deep Learning for Total Shoulder Implant Classification: A Comparative Study.- Deep Facial Phenotyping with Mixup Augmentation.- Context Matters:Cross-domain Cell Detection in Histopathology Images via Contextual Regularization.- TON-ViT: A Neuro-Symbolic AI based on Task Oriented Network with a Vision Transformer.- A new similarity metric for deformable registration of MALDI-MS and MRI images.- Decoding Individual and Shared Experiences of Media Perception using CNN architectures.- Revolutionizing Cancer Diagnosis through Hybrid Self-supervised Deep Learning: EfficientNet with Denoising Autoencoder for Semantic Segmentation of Histopathological Images.- Baseline Models for Action Recognition of Unscripted Casualty Care Dataset.- Web-based AI System for Medical Image Segmentation.- A new approach for identifying skin diseases from dermatological RGB images using source separation.- Pseudo-SPR map Generation from MRI using U-Net Architecture for Ion Beam Therapy Application.- Generalised 3D Medical Image Registration with Learned Shape Encodings.- Retinal Image Screening with Topological Machine Learning.- Neural Network Pruning for Real-time Polyp Segmentation.- A Novel Approach to Breast Cancer Segmentation using U-Net Model with Attention Mechanisms and FedProx Algorithm.- Super Images - A New 2D Perspective on 3D Medical Imaging Analysis.
| Erscheinungsdatum | 02.12.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XI, 340 p. 125 illus., 108 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 539 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Schlagworte | Artificial Intelligence • Classification methods • color image precessing • Computer Networks • Computer systems • computer vision • Deep learning • Image Analysis • image matching • Image Processing • Image Quality • image reconstruction • Image Segmentation • machine learning • Neural networks • pattern recognition • reference image |
| ISBN-10 | 3-031-48592-0 / 3031485920 |
| ISBN-13 | 978-3-031-48592-3 / 9783031485923 |
| Zustand | Neuware |
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