EE 5359 Project Pattern Recognition Diagnostic using Phase Only Correlation technique submitted by Thejaswini Purushotham 1000616811 Fig 1 Experimental setup for medical image diagnostics What has been done already A fingerprint matching algorithm using phase only correlation 1 The proposed technique is particularly effective for verifying low quality fingerprint images that could not be identified correctly by conventional techniques Applications Automated detection of osteoarthritis from knee xray Microcalcification clusters in mammograms Emphysema in CT a lung pathology characterised by destruction of lung lung nodule detection from postero anterior chest radiographs Cryo electron microscopy in structural biology is one of the fields which requires fully automated object detection techniques Simulation Results Fig2 Correlation graph for two similar images length of the peak 1 Results for illumination invariance fig 5 a and b are the X ray images of the same chest with variation in illumination fig 6 Simulation result for the images in fig5 Application of POC for pulmonary emphysema detection There are 80 million patents with developed pulmonary emphysema all over the world 3 million patients are dying every year Studies have shown that lung tissue is about a third of the lung volume has to be destructed before emphysema could be detected 11 Doctors have two methods to diagnose pulmonary emphysema One of the methods is spirometry another is diagnostic imaging Former is a quantitative method however we cannot make an early detection of the disease The classical method of CT image objective evaluation is the PI pixel index method Emphysema shows up on CT as areas with low attenuation coefficients with abnormal distribution By determining the number of pixels with low attenuation emphysema can be detected PI determines the average number of pixels with lower attenuation than the limit value lim Fig 9 Subject A normal lung These images show homogeneous distribution of air in the lung The white dots represent areas with lower attenuation values than 950 HU 930 HU and 910 HU respectively The calculated percentages are 3 5 and 10 13 Fig 10 Subject C severe emphysema There is an obvious destruction ofthe lung parenchyma Pixel indexes 34 48 and 62 13 Issues with PI method The PI method is a good well known measure of emphysema But it is not able to detect emphysema in cases in which emphysema and fibrosis occur at the same time This is because fibrosis tends to increase the attenuation co efficient of pixels whereas emphysema tends to reduce the attenuation co efficient of pixels To reduce the health risk from exposure to radiation while making a CT scan it is desirable to use a radiation dose that is as low as possible However the constraint on irradiation dose leads to considerable noise in CT scans Radiation dosages directly influence the PI index Fig 11 Coronal slice and its accompanying emphysema map calculated for a threshold of 930 HU a b Scan with clinical radiation dose PI 13 3 c d Approximately corresponding slice of a scan of the same patient with a ten times lower radiation dose PI 15 8 Fig 12 1a 1b 1c Simulation results for emphysema detection Fig 123 Simulation results for emphysema progression 4a is the image of a healthy individual 4b 4c and 4d are images of the emphysema in different progressive stages 4e shows that there 11 7 difference between 4a and 4b 4f shows that there is 58 difference between 4b and 4c 4g shows that there is 02 change between 4c and 4d POC method gives a direct mapping between the number of affected pixels and the percentage of visible pixels on the POC map POC method scores over the traditional PI method in terms of the Radiation dosage PI method gives better performance at higher dosages of radiation But the POC method is not dependant on the brightness of the image Hence it is a better method compared to the PI method This technique can be extended and verified over other pathologies like osteoarthritis Lung Nodule Detection and Microcalcification clusters in mammograms References 1 Fazl e Basit M Y Javed and U Qayyum Face Recognition Using Processed Histogram And Phase Only Correlation POC International Conference on Emerging Technologies ICET 2007 pp 238 242 Nov 2007 2 C Nakajima et al Object Recognition And Detection By a Combination Of Support Vector Machine And Rotation Invariant Phase Only Correlation 15th International Conference on Pattern Recognition IEEE Proc Vol 4 pp 787 790 Sept 2000 3 J Z Wang et al Investigation Of A Phase Only Correlation Technique For Anatomical Alignment Of Portal Images In Radiation Therapy Phys Med Biol Vol 41 pp 1045 1058 Jun 1996 4 H Nakajima et al A Fingerprint Matching Algorithm Using Phase Only Correlation IEICE Trans Fundamentals Vol 87 A pp 682 691 Mar 2004 5 S Watanabe T Tanaka and E Iwata Biometric Authentication Using Phase Only Correlation With Compensation Algorithm For Rotation SICE ICASE International Joint Conference Vol 18 pp 37113715 Oct 2006 6 G Yang X YU X Zhuanq Current Status And Development Of Pattern Recognition Diagnostic Methods Based On Medical Imaging IEEE International conference on Networking Sensing and Control Vol 10 pp 567 572 Apr 2008 7 V Zarzoso and A K Nandi Comparison Between Blind Separation And Adaptive Noise Cancellation Techniques For Fetal Electrocardiogram Extraction in Proc IEE Colloquium on Medial Applications of Signal Processing Vol 48 pp 12 18 Oct 1999 8 Z Y Qian et al Medical Images Edge Detection Based on Mathematical Morphology Proc Of IEEE Engineeing in Medicine and Biology 27th Annual Conference pp 6492 6495 Jan 2006 9 WHO Fact sheet website http www who int mediacentre factsheets fs315 en index html 10 R Kobayashi et al Algorithm of Pulmonary emphysema analysis using comparing with expiratory and inspiratory state of CT images SICE Annual Conference 2008 pp 3105 3109 Aug 2008 11 R Uppaluri et al Quantification of pulmonary emphysema from lung computed tomography images Respir Crit Care Med vol 156 pp 248 254 1997 12 Health information website http copd emedtv com emphysema stages ofemphysema p2 html 13 R A Blechschmidt R Werthschutzky and U LOrcher Automated CT image evaluation of the lung A morphology based concept IEEE transactions on medical imaging 14 A Madani C Keyzer and P Gevenois Quantitative computed tomography assessment of lung structure and function in pulmonary emphysema Eur Respir J vol 18 no 4 pp 720 730 2001 15 U Tyl n O Friman M Borga
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