Medical Image Processing - School of ICT, SIIT, Thammasat University

Project Proposal
Medical Image Processing
Group Members
1. Ms.Watcharaporn Sitsawangsopon ID: 5422791509
2. Ms. Maetawee Juladash
ID: 5422772905
Advisor: Dr. Bunyarit Uyyanonvara (Associate Professor)
School of Information, Computer and Communication Technology,
Sirindhorn International Institute of Technology,
Thammasat University
Semester 1, Academic Year 2013
Date: October 3, 2014
Table of Contents
1 Introduction ...................................................................................................................... 1 2 Background....................................................................................................................... 4 3 Objectives ......................................................................................................................... 4 4 Outputs and Expected Benefits ........................................................................................ 5 5 4.1 Outputs ......................................................................................................................... 5 4.2 Benefits ........................................................................................................................ 5 Literature Review ............................................................................................................. 5 Statement of Contribution
By submitting this document, all students in the group agree that their contribution in the
project so far, including the preparation of this document, is as follows:
1. Ms.Watcharaporn Sitsawangsopon
2. Ms. Maetawee Juladash
ID:5422791509
ID:5422772905
50%
50%
Senior Project 2013
Medical Image Processing
1 Introduction
In the medical profession of a facial skin, many patients that come with several
problems and skin lesion types, compare with the amount of doctors that less than the patients
in many countries around the world. So the technology nowadays can help the medical
profession and doctors at least to analyze the problem on each patient's face. This can
decrease the situation of doctors and patients to be in face to face, help the doctors and
patients that resident in different countries, and also decrease the problem of ratio between
doctors and patients.
Technology that can apply to help in medical profession of facial skin in term
of analyze the problem on each patient's face will be about the image processing and face
detection. So mainly thing that necessary is picture of the patient that shown the problem of
facial skin clearly. We observe from several research or previous studies about the Detection
system [1-3], Edge detection [4], Face detection[5], and we know that the picture of patient's
should be the same view point as possible to decrease the error that can happen when detect
the key points (eyes, nose, and mouth) on patient's face. These technologies can find and
detect some problem on the patient's face, for example, detect all spots, acne, wrinkles, etc.
But it was a thoroughly method and difficult because of it maybe detect the unnecessary
details around the patient's face, also include the background of the picture that use to
analyze.
The original images and ground truth images experiment methods of blob
detection.
Position mark images
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Ground truth images
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Senior Project 2013
Medical Image Processing
The images data in the real world position mark of the experiment method of wrinkles
detection.
Original images (1)
Mark position images (1)
Original images (2)
Mark position images (2)
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Original images (3)
Original images (4)
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Medical Image Processing
Mark position images (3)
Mark position images (4)
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Medical Image Processing
2 Background
In the globalization, improvement of technology, science, economy, society
and the education provide people to have a better standard of living and lifestyles. Relating to
the development of medical treatment facial skin that people become more attention of beauty
and healthy, it affects to the rapid growth in beauty care industry, especially in now. Because
of the people focus on the important of their owns face would be good looking and still
younger, but the real natural face of people will be change over time. The natural edge was
born on the face as the notification of older. No matter how old you are or what gender you
are. The medical of facial skin became important to treatment them.
The beauty care clinic and hospital found the average number of medical
treatment is less than the patient. The treatments spend a lot of time and couldn’t manage time
for all of them. The doctor communicate with the patient by face to face, and during the
treatment used a paper to retention the result of patient by mark the specific point on the face
such as circle line or straight line. A drawing point on the paper is not accuracy, and hard to
aftercare a result in the next time. Instead of using the traditional way to retention the
information of patient without drawing a mark point by hand. They would have a new
innovation of medical facial skin program, to help a doctor and patient are easier and
comfortable.
Therefore, as research purpose, it is concerned to develop a medical facial skin
for detect a wrinkle on a face, and know which method have the efficient of detect a wrinkle.
The several method have found such as the face detection, edge detection and the blob
detection etc. We would be adapt some path of each method to improve the program, and
detect an image more accuracy. We created an instance element of image to tests our method
and calculate the accuracy of each experiment method.
3 Objectives
The aim of this project is to write a program to read images of medical
profession, the image is about wrinkles problem on the human face. The program will analyze
and correct the detect area of wrinkles. It will not detect other things on the human face. We
want to write this program to use in the medical profession because nowadays we not have
enough doctors because amount of doctors less than the amount of patients. So, it’s difficult
between them to be in the situation of face-to-face to discuss and cure the problems on the
patient's face. This program can help that doctors no need to meet their patients, it use only
the image of patient's face then program will detect the wrinkles and display the image in the
format that we called "ground truth" to show only the wrinkles area. So, doctors no need to
analyze the problems by themselves, they will use the ground truth and can know
immediately how to cure their patient's problems.
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Medical Image Processing
4 Outputs and Expected Benefits
4.1 Outputs
The output that we want is ground truth image of patient's face from detected
process. The image will show only the line of wrinkles on the patient's face correctly. So, the
important thing that we concern is how to write a program that can read and detect only the
wrinkles on the patient's face because the images of patients is composition of face, hair,
background, etc. So, we want to make sure that program will not detect something else that
not a wrinkle. We learn from the previous researches that maybe program will detect some
key point on the human face (eyes, nose, and mouth) and also hairs that have a line shape
similar to the wrinkles The direction of human face also can effect to the program that it
limited for program to analyze the image. Every images that import to the program, the
human face have to be in the same direction and the best is the human face that look straight
to the camera because it easier to the program to read and detect the wrinkles.
4.2 Benefits
Our project, we write a useful program for the medical profession, especially
in facial skin line. The program will useful with doctors to analyze the methods to cure their
patient's problem by using the ground truth image from program that show the lines of
wrinkles on patient's face. This can decrease the problem that nowadays we lack of doctors
and they not have a chance to discuss or analyze the patient's problems. Doctors can use the
ground truth image from program to follow up the change of the patient's problem in every
period of times, they can know that the problems is better or not by compare the ground truth
images to see the changes of the wrinkles.
The future development of our method can apply with the smart phone on the
application photo feature. The program will detect the wrinkles on human face then it can
develop to blend/blurred the wrinkles that program detected to make the images more
beautiful.
5 Literature Review
[1] Chuan-Yu, Shang-Cheng Li, Pau-Choo Chung, Jui-Yi Kuo, Yung-Chin Tu. "Atomatic
Facial Skin Defect Detection System." Dept. of Computer Science & Information
Engineering, National Yunlin University of Science & Technology, Taiwan. pp.527-532,
2010.
[2] Hideaki Fujii, Takashi Yanagisawa, Masanori Mitsui, Yuri Murakami, Masahiro
Yamaguchi, Nagaaki Ohyama, Tokiya Abe, Ikumi Yokoi, Yoshie Matsuoka, and Yasuo
Kubota. "Extraction of acne lesion in acne patients from Multispectral Images". Annual
International IEEE EMBS Conference Vancouver, British Columbia, Canada. pp.4078-4081,
2008.
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[3] Siddharth K, Madan and Kristin J, Dana. "Learning-Based Detection of Acne-like Regions
Using Time-Lapse Features". Department of Electrical and Computer Engineering, Rutgers
University NJ, USA. 2011.
[4] Digital Image Processing (Other Methods of Edge Detection). Website (accessed by
internal search), Rice University:
http://www.owlnet.rice.edu/~elec539/Projects97/morphjrks/moredge.html (accessed
September 25,2014
[5] Phannapat S, Watcharaporn S, Maetawee J, Guntachai O. "Face Detection" School Of
Information Computer and Communication Technology Sirindhorn International Institute of
Technology, Thammasat University, Thailand. 2013.
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