Jiunn-Lin Wu, PhD

6638 Digital Image Processing (影像處理)

• Course Time:  Tue 13:10-16:00

• Classroom: AT338 

• Course Outlines: This course covers fundamental concepts and methods in digital image processing and their applications. The course is outlined as:

  • 1 Introduction

  • 2 Digital Image Fundamentals

  • 3 Intensity Transformations and Spatial Filtering

  • 4 Filtering in the Frequency Domain

  • 5 Image Restoration and Reconstruction

  • 6 Wavelet and Other Image Transforms

  • 7 Color Image Processing

  • 8 Morphological Image Processing

  • 9 Image Segmentation

  • 10 Deep Learning

  • 11 Image Classification and Object Detection with Convolutional Neural Networks.

• Textbook: "Digital Image Processing", by R. C. Gonzalez and R. E. Woods, 4th Edition, Pearson (開發), 2017.

• Reference Books:  "

  • Digital Image Processing Using MATLAB", 2nd Edition, by Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, 
    McGraw-Hill, 2009.

  • "Artificial Intelligence" by Leonardo Araujo dos Santos. 2018.

  •  "Hands-On Computer Vision with TensorFlow 2", by Benjamin Planche and Eliot Andres, Packt Publishing, 2019.

• Lecture Notes: Chapter0, 關於PPT授課著作權, Chapter1, Chapter2, Chapter3,  Chapter5, Chapter6, Chapter9, Chapter10, Chapter12

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1391 Medical Image Analysis (醫學影像分析)

• Course Time:  Thu 13:10-15:00

• Classroom: IA724

• Course Outlines: This course covers fundamental concepts and methods in digital image processing and their applications. The course is outlined as:

  • Introduction

  • Digital Image Fundamentals

  • Intensity Transformations and Spatial Filtering

  • Image Segmentation I: Edge Detection, Thresholding, and Region Detection

  •  Image Segmentation II: Active Contours: Snakes and Level Sets

  • Feature Extraction

  • Image Pattern Classification

  • Introduction to Deep Learning

  •  Unet Architecture

  •  Medical image analysis with Deep learning

• Textbook: "Digital Image Processing", by R. C. Gonzalez and R. E. Woods, 4th Edition, Pearson (開發), 2017.

• Reference Books:  "

  • “Deep Learning in Medical Image Analysis, Challenges and Applications” by Gobert Lee and HiroshiFujita, Springer, 2020.

  • “Deep Learning for Medical Image Analysis” by S. Kevin Zhou, Hayit Greenspan, Dinggang Shen, Elsevier Inc., 2017.

  • ”Digital Image Processing Using MATLAB”, R. C. Gonzalez and R. E. Woods, 2nd Edition, Prentice Hall, 2011.

  • ”Artificial Inteligence” by Leonardo Araujo dos Santos. 2018.

  •  ”Hands-On Computer Vision with TensorFlow 2”, by Benjamin Planche and Eliot Andres, Packt Publishing, 2019.

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1382 智慧醫療專題轉譯研究

• Course Time:  Thu 15:10-17:00

• Classroom: IA722

• News:

  • Code

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