Titlebook: Medical Imaging and Computer-Aided Diagnosis; Proceeding of 2020 I Ruidan Su,Han Liu Conference proceedings 2020 Springer Nature Singapore

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A Novel Classification Method of Medical Image Segmentation Algorithm,he means to solve the problem of medical image segmentation but also makes the algorithm classification and summary urgent. At present, a variety of classification methods are mostly based on the characteristics of the algorithm itself. If the classification principle of the algorithm is determined

ASSET

fatty-acids

Optical Micro-scanning Reconstruction Technique for a Thermal Microscope Imaging System,ts that need detailed thermal analysis. Due to the mechanical preparation of the system, working vibration, external environment and other factors of interference, which will affect the precision of the micro-scanning system, Causing the micro-displacement of the four images acquired by the system d

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A Survey for Traditional, Cascaded Regression, and Deep Learning-Based Face Alignment,solve the face alignment problems. These methods are classified into three categories: traditional algorithms, cascade based on regression algorithm and deep learning-based algorithm. There are still some problems existing that processing of large pose and small pose, processing of different angles

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Automatic Detection and Counting of Malaria Parasite-Infected Blood Cells,ural network and a feature- based counting process. Current approaches for object detection or counting often rely on prior knowledge of certain salient features of the to-be-identified objects or require time-consuming pre-processing. For this reason, many detection problems, for example infected c

Frequency-Range

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Performance Analysis of Different 2D and 3D CNN Model for Liver Semantic Segmentation: A Review, on abdominal Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) volume images, specifically liver segmentation has a lot of contribution towards clinical decision making for patient treatment. Apart from the many state-of-the-art methods, different cutting-edge deep learning architecture

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Benign

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