Medical Image Analysis
1.Introduction to Medical Image Analysis - PACS / DICOM / Visualization
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참고: https://www.edwith.org/medical-20200327/joinLectures/30437 (컴퓨터비전, 머신러닝, 딥러닝을 이용한 의료영상분석 edwith)
2.Introduction to Medical Image Analysis - Image Acquisition
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3.Medical Image Classification - Advanced CNNs
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참고: https://www.edwith.org/medical-20200327/joinLectures/30437 (컴퓨터비전, 머신러닝, 딥러닝을 이용한 의료영상분석 edwith)
4.Medical Image Classification - Feature selection using L1 regularization
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5.Medical Image Classification - Feature selection using Entropy / Mutual information
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6.Medical Image Segmentation - Otsu thresholding
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7.Medical Image Segmentation - Morphological processing
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8.Medical Image Segmentation - Region growing / Watershed algorithm
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9.Medical Image Segmentation - Segmentation using graph model
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참고: https://www.edwith.org/medical-20200327/joinLectures/30437 (컴퓨터비전, 머신러닝, 딥러닝을 이용한 의료영상분석 edwith)
10.Medical Image Segmentation - Active contour model
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11.Atlas based method / Label fusion
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12.Medical Image Segmentation - Principle Component Analysis (PCA)
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13.Medical Image Segmentation - Active shape model
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14.Medical Image Segmentation - Advanced CNNs
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15.Medical Image Registration - Transformation matrix in 2D
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16.Medical Image Registration - Transformation matrix in 3D
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17.Medical Image Registration - Warping / Interpolation
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18.Medical Image Registration - Similarity measure
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19.Medical Image Registration - Registration using main axis
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20.Medical Image Registration - Non-rigid registration via ICP
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참고: https://www.edwith.org/medical-20200327/joinLectures/30437 (컴퓨터비전, 머신러닝, 딥러닝을 이용한 의료영상분석 edwith)
21.Medical Image Registration - Non-rigid registration via deformable model
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참고: https://www.edwith.org/medical-20200327/joinLectures/30437 (컴퓨터비전, 머신러닝, 딥러닝을 이용한 의료영상분석 edwith)