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Titlebook: Medical Imaging and Computer-Aided Diagnosis; Proceedings of 2022 Ruidan Su,Yudong Zhang,Alejandro F Frangi Conference proceedings 2023 Th

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Lung CT Analysis Using 3D Disparity-Regularised Block Matching for Stereotactic Ablative Body Radiotean squared error (0.0029), and peak signal-to-noise ratio (46.6). Thus providing a quantitative approach to the clinicians aiding in identifying and quantifying the clinically significant geometrical changes, eventually characterising the tumour degradation or pulmonary fibrosis in terms of volumetric and shape changes.
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Small Animal Imaging: Iterative Algorithms Combined with Regularization Schemes, an Application to arenzo-like phantom, taking into account a rotated camera of a standard small animal PET system, is used. Results show that reconstruction methods combined with MRP gives a better image quality for all sized objects. The multiplicative factor in MRP is small while in TV can be over 0.1. Image resolution is a function of reconstruction approach.
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Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Nerast. Then, a dual sided multi-scale convolutional neural network (DSMS-CNN) model is proposed to classify subjects as either normal cognition or PDD based on both hemispheres of the cBF together. Ablation studies and comparison experiments with state-of-the-art CNN models show that DSMS-CNN can achieve promising and superior performance.
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Conference proceedings 2023and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation. .
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Conference proceedings 2023non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging.  .Given its coverage, the book provides both a forum
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NuRISC: Nuclei Radial Instance Segmentation and Classificationeads. A compound classification loss function is used that minimizes loss by assigning weighted loss to each class according to type occurrence frequency thus mitigating major class imbalance issues existing in most of publicly available nuclei datasets.
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