Skin Lesion Segmentation Using Image Bit-Plane Multilayer Approach

Maria Rizzi,Cataldo Guaragnella

doi:10.3390/app10093045

Abstract

The establishment of automatic diagnostic systems able to detect and classify skin lesions at the initial stage are getting really relevant and effective in providing support for medical personnel during clinical assessment. Image segmentation has a determinant part in computer-aided skin lesion diagnosis pipeline because it makes possible to extract and highlight information on lesion contour texture as, for example, skewness and area unevenness. However, artifacts, low contrast, indistinct boundaries, and different shapes and areas contribute to make skin lesion segmentation a challenging task. In this paper, a fully automatic computer-aided system for skin lesion segmentation in dermoscopic images is indicated. Adopting this method, noise and artifacts are initially reduced by the singular value decomposition; afterward lesion decomposition into a frame of bit-plane layers is performed. A specific procedure is implemented for redundant data reduction using simple Boolean operators. Since lesion and background are rarely homogeneous regions, the obtained segmentation region could contain some disjointed areas classified as lesion. To obtain a single zone classified as lesion avoiding spurious pixels or holes inside the image under test, mathematical morphological techniques are implemented. The performance obtained highlights the method validity.

Highlights

The adoption of digital technology in the healthcare environment is growing steadily each year with forecasts of further increments in the near future
It is considered the deadliest type of skin cancer with a high death rate if diagnosed too late: Melanoma accounts for approximately 75% of deaths associated with skin cancer [10]
The performance of the implemented procedure was assessed by comparing the CADe outputs with the ground truths indicated by expert clinicians, which are collected inside the used database

Summary

Introduction

The adoption of digital technology in the healthcare environment is growing steadily each year with forecasts of further increments in the near future. The overall health of people continues to improve in many ways as a consequence of advances in medical technology, research, and resources set aside to public health and education [3]. Devices, such as sensors, communication systems, and computers, allow the implementation and diffusion of proper and suitable technologies for acquiring, processing, analyzing, and transmitting health-related data [4,5]. Skin melanoma incidence has grown about 15% over the last 10 years compared with the previous decade [9].

Methods

Results

Conclusion