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  Table of Contents  
LETTER TO THE EDITOR
Year : 2017  |  Volume : 8  |  Issue : 6  |  Page : 513-514  

Noise removal in dermoscopic images using a novel software


1 Department of Dermatology, Venereology and Leprosy, Yenepoya Medical College, and Yenepoya Research Center, Yenepoya University, Deralakatte, India
2 Department of Computer Science, Mangalore University, Konaje, Mangalore, Karnataka, India

Date of Web Publication14-Nov-2017

Correspondence Address:
Manjunarh M Shenoy
Department of Dermatology, Venereology and Leprosy, Yenepoya Medical College, Yenepoya University, Deralakatte, Mangalore - 575 018, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/idoj.IDOJ_417_16

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How to cite this article:
Hegde PR, Shenoy MM, Shekar B H. Noise removal in dermoscopic images using a novel software. Indian Dermatol Online J 2017;8:513-4

How to cite this URL:
Hegde PR, Shenoy MM, Shekar B H. Noise removal in dermoscopic images using a novel software. Indian Dermatol Online J [serial online] 2017 [cited 2019 Aug 18];8:513-4. Available from: http://www.idoj.in/text.asp?2017/8/6/513/218344



Sir,

Dermoscopy enables magnified in vivo visualization of subcuticular features invisible to the naked eye.[1] It may be performed manually or with digital systems such as video camera to archive the images over a period of time.[2] Presence of the hairs, ruler markings, and air bubbles may hamper the dermoscopic image's evaluation.[2],[3] Thin hairs generally do not interfere in the diagnosis but thick hairs can be a distraction. In technical terms, these are called “noise,” and removing noise will not affect the diagnosis and may increase the diagnostic accuracy.

Assistance of certain software can aid us to remove the noise. This involves several steps. We have employed such a technique in one of our dermoscopic images of psoriasis [Figure 1]a. We used polarized dermoscopic images using Hein Delta 20 plus with Sony Cyber-shot DSC-W830 camera. Initially, original image was converted to an 8-bit color image and edge detection method was implemented to detect the artifacts; then, the morphological feature detection method was used to segment the areas detected by edge detection method [Figure 1]b. Finally, we designed our own method to find the noise region and to mask or replace that region [Figure 1]c. The following code replaced the noise region by the neighboring pixels. This enabled us to obtain a final image that is devoid of the noise and without any disturbance in the required dermoscopic features.
Figure 1: (a) Original dermoscopic image, (b) artifacts segmented image, (c) output image

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The concept of noise removal is old but its utility has been explored for all dermoscopic images. Software removes thick hairs without affecting the diseased region [Figure 2]. Image enhancement algorithms implemented in the software improves the output image quality, which helps in better illustration and archival. It utilizes a user friendly interface (GUI) and faster processing using an endogenously designed software which is available on the internet. Time taken for the software for image processing ranges from 30 seconds to 3 minutes depending on the image size and presence of noise. There is no need for any sophisticated computer skills. The proposed tool will not remove hair at ill-focused region and very thick hairs; however, we are working towards incorporating these features too.
Figure 2: (a) Original dermoscopic image, (b) output image

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We propose this software utility for the dermatologists to increase the diagnostic accuracy of the dermoscopy. This software is available in the university's research centre website (http://yenepoyaresearch.edu.in/Patents_softwares.php).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Braun RP, Rabinovitz HS, Oliviero M, Kopf AW, Saurat JH. Dermoscopy of pigmented skin lesions. J Am Acad Dermatol 2005;52:109-21.  Back to cited text no. 1
    
2.
Huang A, Kwan SY, Chang WY, Liu MY, Chi MH, Chen GS. A robust hair segmentation and removal approach for clinical images of skin lesions. 35th Annual International Conference of the IEEE EMBS; Osaka (Japan); 2013.  Back to cited text no. 2
    
3.
Kiani K, Sharafat AR. E-shaver: An improved DullRazors for digitally removing dark and light-colored hairs in dermoscopic images. Comput Biol Med 2011;41:139-45.  Back to cited text no. 3
    


    Figures

  [Figure 1], [Figure 2]



 

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