Presentation is loading. Please wait.

Presentation is loading. Please wait.

Detecting the excessive activation of the ciliaris muscle on thermal images Balázs Harangi Faculty of Informatics, University of Debrecen SSIP 2009, 10.

Similar presentations


Presentation on theme: "Detecting the excessive activation of the ciliaris muscle on thermal images Balázs Harangi Faculty of Informatics, University of Debrecen SSIP 2009, 10."— Presentation transcript:

1 Detecting the excessive activation of the ciliaris muscle on thermal images Balázs Harangi Faculty of Informatics, University of Debrecen SSIP 2009, 10 July 2009, Debrecen, Hungary

2 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 2 Overview Aim of research: Our primary aim in this field is to set up a system which is able to alert, if the activity of the ciliaris muscle is suspected to be excessive. The main line of the research is to detect the extra quantity of heat caused by the excessive activity of the ciliaris muscle on thermal images. Final aim is to realize a system that is able to automatically diagnose.

3 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 3 Background of the research The ciliaris muscle A ring shaped muscle surrounds the crystalline lens in the eye. The muscle contracts when someone looks at a near object and relaxes when someone looks far.

4 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 4 Background of the research Problem of the ciliaris muscle The muscle does not relax in all cases, and thus, the crystalline lens does not flatten perfectly. The traditional ophthalmologic examination by a refractometer may provide a false dioptre value in this case. Fault of measurement cases vision improvement, head-ache, reading and other sight disorder.

5 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 5 Background of the research Aim and possible exploitation of the research Since the ciliaris muscle is close to the exterior surface of the eye, we have the opportunity to take advantage of thermal monitoring of it.

6 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 6 Steps of Research Images captured by Somatoinfra 384 x 288 pixels, 8-bit intensity, 256-color images

7 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 7 Steps of Research The usage of grayscale images Usually color palettes are applied for displaying in order to let smaller differences to be easily detectable for a human observer, but for simplicity, we change the color representation to grayscale.

8 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 8 Steps of Research Image normalization The temperature of the skin depends on the external weather or the internal temperature of the examine room. For these reasons, we inserted a normalization step into our system to eliminate these differences.

9 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 9 Steps of Research Localization of the eye We modeled the eyes with ellipses which are subdivided into subregions. Thus, we can focus to the interesting regions only.

10 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 10 Steps of Research First-order statistical descriptors: WALK RUN Mean of intensity histogram: Variance of intensity histogram: Skewness of intensity histogram: Kurtosis of intensity histogram : Energy of intensity histogram : Entropy of intensity histogram :

11 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 11 Steps of Research Training and classification We gain 144 dimensional feature vectors per eye if all the subregions are involved. After then we considered the kNN classifier (with k=10) to decide whether a test image was labeled as healthy or diseased.

12 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 12 Program development Program language: The sourcecode is written in Matlab, we used the following tools: –Image Processing Toolbox: imread(); imshow() imellipse(); vertex(); poly2mask() graycomatrix(); graycoprops() –Statistics Toolbox: skewness(); kurtosis() –and Bioinformatics Toolbox : knnclassify()

13 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 13 Functions: Normalization of heat scale Definition of region of eyes Extraction of features Classification Program development

14 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 14 Conclusion and Discussion Database Our initial training database contains 20 healthy and 20 diseased images manually labeled by a clinical expert. (diseased)(healty)

15 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 15 Conclusion and Discussion Result: Our simple algorithm is tested on small databased. Result of this test: FPFNOverall Our method (selected regions)3/202/2075% Our method (all regions)4/203/2065%

16 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 16 Conclusion and Discussion Fault results: True positiveFalse positive

17 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 17 Conclusion and Discussion Fault results: True negativeFalse negative

18 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 18 Conclusion and Discussion Summary Basic functions of the finally system are ready and acting. Results of the decision are good enough, but we have to refine. Plans A current database should be extended More specify results Automatic location of the eye region Finding the critical point of eye on normal picture (corner, pupil, ciliaris muscle) Find an appropriate physical model to get rid of thermal distortion of orbit.

19 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 19 Decision of ophthalmologist One way to more exact results: The practical diagnostics is based on comparing the thermal value of the ciliaris muscle with the centre of the cornea.

20 Overview Background of the research Steps of research Program development Conclusion and Discussion Decision of ophthalmologist 2015. 05. 15. 19:15 20 Thank you! Thank you for your attention!


Download ppt "Detecting the excessive activation of the ciliaris muscle on thermal images Balázs Harangi Faculty of Informatics, University of Debrecen SSIP 2009, 10."

Similar presentations


Ads by Google