A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

<div><p>Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts.</p></div

Visual inspection of different vessel segmentation methods using STARE database.

<p>(a) RGB input image. (b) Manual segmented image. (c) Proposed method final image. (d) Dai et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref040" target="_blank">40</a>]. (e) Azzopardi et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref035" target="_blank">35</a>]. (f) Bankhead et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref030" target="_blank">30</a>]. (g)Vlachos and Dermatas [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref041" target="_blank">41</a>]. (h) Martinez-Perez et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref017" target="_blank">17</a>].</p

Proposed method main processing steps for retinal blood vessel segmentation.

<p>(a) RGB image from <b>DRIVE</b> database. (b) Green Channel. (c) CLAHE. (d) Morphological filters. (e) Thin vessel enhanced image. (f) Wide vessel enhanced image. (g) Otsu global thresholding output image. (h) Fused image of thin enhanced image and Otsu global thresholding output image. (i) Otsu local thresholding to enhance thin vessels (j) Postprocessed final binary image.</p

Pictorial results of different retinal blood vessel segmentation techniques on pathological image of DRIVE dataset.

<p>(a) RGB input image. (b) Manual segmented image. (c) Proposed method. (d) Azzopardi et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref035" target="_blank">35</a>]. (e) Dai et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref040" target="_blank">40</a>]. (f) Bankhead et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158996#pone.0158996.ref030" target="_blank">30</a>].</p

Performance comparison of AUC with existing techniques.

<p>Performance comparison of AUC with existing techniques.</p

Comparison of the setting of parameter <i>σ</i> on different scales.

<p>(a) Thin vessel enhanced image. (b) Thin binary Image. (c) Thick vessel enhanced image. (d) Thick binary image.</p

Visual results of different thresholding techniques.

<p><b>(a) Proposed Otsu method.</b> (b) TILT. (c) K-means. (d) Moment-preserving thresholding. (e) Niblack local thresholding. (f) Fuzzy ISODATA algorithms.</p

Accuracy (Acc), Sensitivity (Sn) and Specificity (Sp) results of proposed method for 20 retinal images of the DRIVE and the STARE datasets.

<p>Accuracy (Acc), Sensitivity (Sn) and Specificity (Sp) results of proposed method for 20 retinal images of the DRIVE and the STARE datasets.</p

Theoretical and experimental investigation of <i>N</i>-alkyl substituted <i>bis</i>-imidazolium salts and their binuclear <i>N</i>-heterocyclic carbene silver acetate complexes

Our research centers on structural, biological, and electronic properties of N-heterocyclic carbene salts and their silver acetate-based complexes. After theoretical calculations, compounds were synthesized. In the DFT studies, functional of B3LYP was used with the basis set of 6-31++G and LanL2DZ for salts and complexes, respectively. The most stable structures were calculated and non-covalent interactions evaluated. Electronic parameters were checked while calculating their HOMO and LUMO energies so that their biological potential can be evaluated. Density of states were studied to check the electronic densities. Among all compounds, 3 was considered the best with energy gap of 0.121 eV. As all eight compounds have very reasonable HOMO-LUMO energy gaps they were considered feasible to synthesize and have strong biological potentials. Compounds were characterized by FT-IR and NMR spectroscopy.</p

Computation time comparison of various techniques.

<p>Computation time comparison of various techniques.</p