Wireless capsule endoscopy video classification using an unsupervised learning approach

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1 Journal of Image and Graphics Vol. 16 No. 11 Nov TP A Bill P. Buckles. J Bill P. Buckles WCE WCE WCE SIFT plsa WCE Wireless capsule endoscopy video classification using an unsupervised learning approach Feng Wengang 1 Gao Jun 1 Bill P. Buckles 2 Wu Kewei 1 1 School of Computer and Information Hefei University of Technology Hefei China 2 Department of Computer and Science University of North Texas Denton USA Abstract Since Wireless Capsule Endoscopy WCE is a novel technology for recording the videos of the digestive tract of a patient the problem of segmenting the WCE videos of the digestive tract into sub-images corresponding to the mouth stomach small intestine and large intestine regions is not well addressed in the literature. A few papers addressing this problem use a supervised learning approach that presumes availability of a large database of correctly labeled training samples. Considering the difficulties in procuring sizable WCE training data sets needed for achieving high classification accuracy we introduce an unsupervised learning approach that employs Scale invariant feature transform SIFT with color information for extraction of local features and uses probabilistic latent semantic analysis plsa model for data semantic analysis. Our results indicate that this method compares well in classification accuracy with the state-of-the-art supervised classification approach to WCE image classification. Keywords video classification unsupervised learning approach probabilistic latent semantic analysis plsa Scale invariant feature transform SIFT 0 WCE WCE DARPA-BAA wengang. feng@ gmail. com

2 2042 www. cjig. cn Spyridonos 1 WCE /s 12 Cunha WCE 2 3 Mackiewicz ~ 2 WCE 5 WCE WCE WCE WCE WCE WCE WCE plsa 13 SIFT 14 plsa SIFT 1 WCE 1 WCE ROI WCE 1 SIFT bag-ofwords SIFT SIFT WCE 2 1 Fig. 1 Four parts of digestive SIFT Difference of Gaussians MPEG % R G B H S V

11 2043 2 b 16 8 128 z k Z = z 1 z K 2 Fig. 2 Image gradient and keypoint descriptor d j plsa SIFT d j WCE D z k RGB w i HSV 4 K hue saturation value 4.

3 b z k Z = z 1 z K 2 Fig. 2 Image gradient and keypoint descriptor d j plsa SIFT d j WCE D z k RGB w i HSV 4 K hue saturation value Coimbra 16 MPEG-7 plsa HSV WCE Hofmann 23 plsa d j p z HSV 3 k d j p z k p w SIFT SIFT i z k z k p w i d j = Σ K p z k p w i z k p z k d j 1 k = 1 EM RGB p z k p w i z k p z k d j HSV RGB 3 L = logp D W = 384 SIFT M N n w i d j logp w i d j i = 1 j = 1 bag-of-words 2 BOW BOW n w i d j w i d j EM E z k P z k d i w j = p z k P w i z k P d i z k P w j z l P z l d i K M E WCE P z k d i w j p z k P w i z k P d i z k K Σ M n w i d j P z k d j w i i = 1 j = 1 p z k = 4 2 plsa plsa M d j D = d 1 d M w i W = w 1 w N N W Σ K l = 1 Σ M n w i d j i = 1 j = 1

4 2044 www. cjig. cn 16 P w j z k = P z k d i = n d i w j P z k d i w j i = 1 Σ M n d i w m P z k d i w m m = 1 i = 1 Σ M n d i w j P z k d i w j j = 1 n d i 5 6 EM p z k p w i z k 4 p z k d j 1 EM L L p z k d j 3 p z k d j 3 plsa WCE P1 P2 P3 P4 4 WCE 3 WCE WCE Fig. 3 Flowchart of WCE video classification by unsupervised learning algorithm 1 Fig. 4 4 WCE WCE video classification result SIFT SIFT 4 3 SIFT

5 RGB-SIFT plsa Tab Experiment 1 results comparison P1 /P2 P2 /P3 P3 /P4 SIFT-SVM-lin SIFT-SVM-rad SIFT-pLSA / / SVM-Radial / 3 SVM-Linear SVM 3. 3 SVM plsa RGB-SIFT plsa SVM SIFT SVM bag-of-words K plsa WCE plsa SIFT RGB-SIFT HSV-SIFT 2 RGB-SIFT Tab Experiment 2 results comparison P1 /P2 P2 /P3 P3 /P4 plsa-rgb-sift ~ Tab Experiment 2 results comparison P1 /P2 P2 /P3 P3 /P4 Gray-SIFT HSV-SIFT RGB-SIFT SVM SIFT 3 RGB-SIFT Fig. 5 plsa Mackiewicz 8 8 SVM 1 4 LBP plsa SIFT HS Hue Saturation plsa 3 RGB-SIFT plsa SIFT SVM SVM SIFT 5 3 Experiment 3 results comparison

6 2046 www. cjig. cn 16 SIFT SVM SIFT SIFT RGB SIFT HSV SIFT SVM Press References 1 Krishnan S Wang P Kugean C et al. Classification of endoscopic images based on texture and neural network C / /Proc. of 23rd Annual IEEE Int. Conf. in Engineering in Medicine and Biology. Washington DC IEEE Press Gay G Delvaux M Key J. The role of video capsule endoscopy in the diagnosis of digestive diseases A review of current possibilities J. Endoscopy Swain P. Wireless capsule endoscopy and Crohn s disease J. Gut Culliford A Daly J Diamond B et al. The value of wireless capsule endoscopy in patients with complicated celiac disease J. Gastrointestinal Endoscopy Maieron A. Multicenter retrospective evaluation of capsule endoscopy in clinical routine J. Endoscopy Coimbra M T Cunha J P S. MPEG-7 visual descriptorscontributions for automated feature extraction in capsule endoscopy J. IEEE Transactions on Circuits and Systems for Video Technology Boulougoura M Wadge E Kodogiannis V S et al. Intelligent systems for computer-assisted clinical endoscopic image analyses C / /Proc. of 2nd Int. Conf. Biomed. Engineering. Innsbruck Austria IEEE Press Mackiewicz M Berens J Fisher M. Wireless capsule endoscopy color video segmentation J. IEEE Transactions on Medical Imaging Howarth P Yavlinsky A Heesch D et al. Medical image retrieval using texture locality and color C / /Proc. Cross Language Evaluation Forum. Washington DC USA IEEE Press Wang P Krishman S Kugean C et al. Classification of endoscopic images based on texture and neural network C / / Proc. 23rd Annu. Int. Conf. IEEE Eng. Med. Biol. Sci. Washington DC USA IEEE Press Spyridonos P Vilarino F Vitria J et al. Anisotropic feature extraction from endoluminal images for detection of intestinal contractions C / /Proc. MICCAI. Washington DC USA IEEE 12 Cunha J Coimbra M Campos P et al. Automated topographic segmentation and transit time estimation in endoscopic capsule exams J. IEEE Trans. Medical. Image Hofmann T. Unsupervised learning by probabilistic latent semantic analysis J. Machine Learning Lowe D G. Distinctive image features from scale-invariant keypoints J. International Journal of Computer Vision Berens J. Image Indexing Using Compressed Color Histograms M. Springer-Verlag Norwich Spinger Coimbra M Campos P Cunha J P S. MPEG-7 visual descriptors Contributions for automated feature extraction in capsule endoscopy J. IEEE Trans. Circuits Syst. Video Technology Jurie F Triggs B Creating efficient codebooks for visual recognition C / /Proceedings of International Conference on Computer Vision. Washington DC USA IEEE Press Bosch A Zisserman A Muoz X. Scene classification using a hybrid generative discriminative approach J. IEEE Transactions on Pattern Analysis and Machine Intelligence Linde Y Buzo A Gray R M. An algorithm for vector quantizer design J. IEEE Transactions on Communications Oliva A Torralba A. Modeling the shape of the scene A holistic representation of the spatial envelope J. International Journal of Computer Vision Niebles J Wang H Li F. Unsupervised learning of human action categories using spatial-temporal words J. International Journal of Computer Vision Lloyd S P. Least square quantization in PCM J. IEEE Transactions on Information Theory Li Feifei Perona P. A Bayesian hierarchical model for learning natural scene categories C / /IEEE Conference on Computer Vision and Pattern Recognition. Washington D C USA IEEE Press

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