An efficient algorithm for boundary tracing and feature extraction

Detection of tubule boundaries based on circular shortest path and polar-transformation of arbitrary shapes

In studies of germ cell transplantation, counting cells and measuring tubule diameters from different populations using labelled antibodies are important measurement processes. However, it is slow and sanity grinding to do these tasks manually. This paper proposes a way to accelerate these processes using a new image analysis framework based on several novel algorithms: centre points detection of tubules, tubule shape classification, skeleton-based polar-transformation, boundary weighting of polar-transformed image, and circular shortest path smoothing. The framework has been tested on a dataset consisting of 27 images which contain a total of 989 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually and the novel approach can achieve a better performance than two existing methods.

Automatic detection of irregular borders in melanoma and other skin tumors

An irregularity index previously developed is applied to detect irregular borders automatically in skin tumor images, particularly malignant melanoma. The irregularity index is used to classify various tumor borders as irregular or regular. This procedure processes tumor images with borders automatically determined by a radial search algorithm previously described. Potential use of this algorithm in an in vivo skin cancer detection system and errors expected in the use of the algorithm are discussed.

Quick method of measuring the furrows distribution on skin surface replicas

A fast method of measuring the distribution of furrows can be obtained via the analysis of TV camera images of skin replicas. These replicas are either negative (or direct) or positive. Reflected or transmitted light is used, depending on the type of replica. Each point of the matrix (256 x 256 pixels) is digitised over 6 bits (64 levels) and treated by a personal computer (IBM AT or PC). With such an image, it is not possible to obtain significant results without eliminating noise and enhancing the furrows. Specific software is written in processor language 8086 to obtain a real time system. The distribution of skin furrows is quantified for several interesting cases such as the ageing of the skin or the effect of stress.