Cattleya Duanggate

Parameter-free optic disc detection

The paper presents a simple, parameter-free method to detect the optic disc in retinal images. It works efficiently for blurred and noisy images with a varying ratio OD/image size. The method works equally well on images with different characteristics which often cause standard methods to fail or require a new round of training. The proposed method has been tested on 214 infant and adult retinal images and has been compared against hand-drawn ground truths generated by experts. It displays consistently high OD detection rates without any prior training or adjustment of the parameters.

Medical image blob detection with feature stability and KNN classification

Object detection methods with feature stability along with the use of KNN algorithm are proposed within this paper. A scale-space tree is constructed based on the blobs that were created from a series of images after blurring. Features and spatial information provides the role in scalespace tree construction. After the process of blob extraction, users determine the type of blobs that were detected within the image by distinguishing classes to create ground truth images. Within the same process, KNN algorithm is applied to distinguish classes of the images blob to demonstrate its performance.

Object detection with feature stability over scale space

This paper proposes a novel segmentation method based on the scale space techniques endowed with a feature stability approach. The novelty of the paper is the lifetime of the space-scale blobs measured not only by their presence and disappearance but by the stability of the features characterizing the objects of interest as well. Our numerical experiments show that the algorithm outperforms the conventional space scale algorithm applied to variable size and variable shape objects. The proposed algorithm can be used as a preprocessing step in object or pattern recognition applications to produce seeds for more accurate image segmentation methods such as the snakes or the level set techniques.