segmentation results

7/23/2019 Segmentation Results

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Segmentation of Cysts from OCT images

Dataset: OCT image each of 49 Frames of OPTIMA CYST CHALLENGE.

Vendor: Spectrail Heidelberg Engineering

Slides 3-4 are frame number 1 of bscan1 without Cyst.

Slides 5-6 are frame number 19 of bscan1 with Cyst.

Slides 7-16 are Cyst segmentation results from Bscan_1 of a Spectrail_1

using Infinity Reconstruction of log+gray weight difference.


using Infinity Reconstruction of log+gray weight difference.


using Fuzzy C means Clustering.



Results

De-noised OCT Image: Method OBNLM

Cyst



Nerve Fiber Layer(NFL)

Retinal Pigment Epithelium (RPE)

ROI Drawn of Nerve Fiber Layer and Retinal

Pigment Epithelium layers Using Gradient

Based Spectra Peaks Detection algorithm





Segmented Nerve Fiber Layer and Retinal


Based Spectra Peaks Detection based method





ROI Drawn of Nerve Fiber Layer and Retinal


Based Spectra Peaks Detection algorithm





Segmented Nerve Fiber Layer and Retinal


Based Spectra Peaks Detection based method



Semi-Automatic Segmentation of Cyst



RED Marks are Original Ground truth by Ophthalmologist

Semi-Automated method employed one pixel selected from each cyst to segment

Image: Bscan_1 of Spectrails 1; Frame No: 14



Segmentation result of cysts from Marker points using Infinity Reconstruction Method


Red marked regions are Segmented result and white regions is Ground Truth






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RED M k O i i l G d h b O h h l l i






S t ti lt f t f M k i t i I fi it R t ti M th d






RED M k O i i l G d t th b O hth l l i t






S t ti lt f t f M k i t i I fi it R t ti M th d



Automatic Segmentation of Cyst

Automatic Segmentation of cysts using FCM Clustering Method



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Results and Discussion

• Results: – Results obtained so far using “Mathematical Morphological Infinity

Reconstruction” method on log of gray weight difference matrix showsthat method is robust to differentiate the gradient differencesbetween cyst and retinal Layers.

– Above method fails to achieve accurate segmentation due to smallgradient differences.

– The contour of cyst detection is challenge due to artifacts such asNoise and gray level similarities with Retinal Layers.

– “Fuzzy C Means Clustering” gives better results than log-gray weightdifference matrix method.



Future Work

• Future work to be done: – Improving the “Mathematical Morphological Infinity Reconstruction”

based segmentation either by Mathematical Morphological operations

or Fuzzy C Means clustering.

– Employing Level Set for semi-automatic segmentation of cysts.

– Developing an Automated method using level set contour detection

and inference mechanism.

segmentation results

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