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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7936完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳少傑(Sao-Jie Chen) | |
| dc.contributor.author | Chen-Yu Li | en |
| dc.contributor.author | 李鎮宇 | zh_TW |
| dc.date.accessioned | 2021-05-19T17:59:23Z | - |
| dc.date.available | 2021-07-26 | |
| dc.date.available | 2021-05-19T17:59:23Z | - |
| dc.date.copyright | 2016-07-26 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-07-21 | |
| dc.identifier.citation | [1] Szu, Harold, L. Miao, and H. Qi, 'Thermodynamic Free-energy Minimization for Unsupervised Fusion of Dual-color Infrared Breast Images,' Defense and Security Symposium. International Society for Optics and Photonics, pp.6-11, April 2006.
[2] H.-Y. Hsieh, 'Evaluation and Implementation of Dual-Spectrum IR Spectrogram Diagnostic System on Breast Cancer Detection,' Master Thesis, National Taiwan University, July 2008. [3] C.-Y. Lee, 'Evaluation of Dual-spectrum IR Spectrogram System on Invasive Ductal Carcinoma (IDC) Breast Cancer,' Biomedical Engineering: Applications, Basis and Communications, pp.427-433, June, 2011. [4] A. Belouchrani, K. Abed-Meraim, J.-F. Cardoso, and E. Moulines, 'A Blind Source Separation Technique Using Second-order Statistics,' IEEE Transactions on Signal Processing, vol.45, no.2, pp.434-444, February 1997. [5] J. Friedman, T. Hastie, and R. Tibshirani, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2011. [6] A.-C. Rencher, Multivariate Statistical Inference and Applications, Wiley-Interscience, 1998. [7] http://web.ntpu.edu.tw/~ccw/statmath/M_group_1.pdf [8] http://web.ntpu.edu.tw/~ccw/statmath/M_group_2.pdf [9] http://web.ntpu.edu.tw/~ccw/statmath/M_group_3.pdf [10] http://web.ntpu.edu.tw/~ccw/statmath/M_group_4.pdf [11] http://www.fda.gov/RegulatoryInformation/Guidances/ucm126420.htm [12] https://wwssllabcd.github.io/blog/2013/01/31/how-to-setup-raspberry-pi/ [13] W. Herschel, 'Experiments on the Refrangibility of the Invisible Rays of the Sun,' Philosophical Transactions of the Royal Society of London, vol. 90, pp. 284-292, 1800. [14] S.-Y. Yin, 'Design of a Dual-band Quantum-well IR Spectrogram Readout Circuit,' Master Thesis, National Taiwan University, July 2014. [15] C.-C. Wang, 'A Practical Infrared Image Contrast Enhancement Method,' Master Thesis, National Chiao Tung University, June 2004. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7936 | - |
| dc.description.abstract | 本論文提出一個針對雙波段紅外線頻譜(Dual-band IR Spectrogram)，應用改良的盲源分離演算法(Blind Source Separation Algorithm)進行分析，來判定追蹤乳癌的長期化療之成效。本文採用雙波段紅外線頻譜的原始資料(RAW Data)為輸入檔，進行演算法分析，並針對盲源分離演算法的特性，在過程中運用資料分析進行改良，最後將該演算法加載至本實驗室開發的醫療控管處理器設計進行整合，提供我們一個更便利的管道來體現雙波段紅外線頻譜分析應用於醫療的成果。在標定率方面，該改良演算法設計比其他演算法平均高15%，在癌細胞判斷的正確率方面，該演算法設計比其他演算法平均高10%。 | zh_TW |
| dc.description.abstract | This work presents an application of Blind Source Separation (BSS) Algorithms on Dual-band IR Spectrogram for breast cancer detection, which is used to trace the effect of long-term chemotherapy for breast-cancer patients. We take Dual-band IR Spectrogram’s RAW Data as an input to the BSS algorithms. Also, we plan to integrate this analytical algorithm into the back-end processor of our designed Dual-band IR Sensor and Readout Circuit Platform. This work will provide a more convenient medical application of our Improved Neighbor-based BSS algorithm on Dual-band IR Spectrogram for breast cancer detection. For Demarcating Degree, our Improved Neighbor-based BSS algorithm is approximately 15% better than other algorithms. For Correctness Rate, our improved algorithm approximately increases 10% compared with other algorithms. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-19T17:59:23Z (GMT). No. of bitstreams: 1 ntu-105-R03943139-1.pdf: 3256483 bytes, checksum: a2871bf570fe2900b80db9177eb53417 (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | ABSTRACT i
TABLE OF CONTENTS iii LIST OF FIGURES v LIST OF TABLES vii CHAPTER 1 INTRODUCTION 1 1.1 Motivation 1 1.2 Thesis Organization 2 CHAPTER 2 BACKGROUND 3 2.1 Dual-band IR Spectrogram 3 2.2 Blind Source Separation Algorithms 5 2.2.1 Single Pixel Blind Source Separation Algorithm 5 2.2.2 Neighbor-based Blind Source Separation Algorithm 7 2.3 Machine Learning Models 8 2.3.1 Supervised Learning and Unsupervised Learning 8 2.3.2 Linear Regression Model and Non-linear Regression Model 9 2.4 Breast Cancer Detection 11 2.4.1 Thermal Phenomena of Symptom 11 2.4.2 Critical Temperature and Gradient Temperature 12 2.4.3 Risk Level of Breast Cancer 13 CHAPTER 3 BLIND SOURCE SEPERATION ALGORITHMS 15 3.1 Single Pixel Blind Separation Algorithm 15 3.1.1 Principle of Single Pixel BSS 15 3.1.2 Application of Single Pixel BSS 16 3.1.3 Challenge in Single Pixel Blind Separation Algorithm 16 3.2 Neighbor-based Blind Separation Algorithm 17 3.2.1 Principle of Neighbor-based BSS 17 3.2.2 Application of Neighbor-based BSS 20 3.2.3 Challenge in Neighbor-based Blind Separation Algorithm 21 3.3 Machine Learning Analysis Algorithms 21 3.3.1 Linear Regression Model 21 3.3.2 Augmented Regression Model 22 3.4 Experiment Procedures 23 3.4.1 Specification of SC4000 FLIR Camera 23 3.4.2 Dual-band IR Platform 25 CHAPTER 4 SIMULATION AND EXPERIMENT RESULTS 29 4.1 RAW Data Pre-Processing 29 4.1.1 Histogram Equalization 29 4.1.2 Binary Occupied Histogram Projection 30 4.1.3 Result of Compression 30 4.2 Experimental Results 31 4.2.1 Algorithms used in our Experiments 31 4.2.2 Demarcating Degree 37 4.2.3 Correctness Rate and Error Rate 39 CHAPTER 5 CONCLUSIONS 43 REFERENCE 45 | |
| dc.language.iso | en | |
| dc.title | 應用於雙波段紅外線之乳癌檢測盲源分離演算法 | zh_TW |
| dc.title | Application of Blind Source Separation Algorithms on Dual-band IR Spectrogram for Breast Cancer Detection | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳中平(Chung-Ping Chen),游竹(Yu Chu),林伯星(Bor-Shing Lin) | |
| dc.subject.keyword | 雙波段紅外線影像,盲源分離演算法, | zh_TW |
| dc.subject.keyword | Dual-band IR Spectrogram,Blind Source Separation Algorithm, | en |
| dc.relation.page | 46 | |
| dc.identifier.doi | 10.6342/NTU201601166 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2016-07-22 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
| 顯示於系所單位： | 電子工程學研究所 | |
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| ntu-105-1.pdf | 3.18 MB | Adobe PDF | 檢視/開啟 |
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