Purpose: In this work the problem of automatic segmentation of nuclei in cytological images of thyroid nodules is investigated. Materials and Methods: 50 Fine Needle Aspiration images of thyroid nodules were digitized (768x576x8 bit) using a light microscopy imaging system comprising a Zeiss Axiostar plus microscope connected to a Leica DC 300 F color video camera. An automatic segmentation alg...

In this extended abstract we present our current work concerning the development of minimum description length (MDL) principle based solutions for medical image segmentation problems. Our application is the interpretation of overlapping nuclei in histological images in terms of individual nuclei within a parametric shape family. MDL is a well suited approach for this application as MDL provides...

The segmentation and quantification of cell nuclei are two very significant tasks in the analysis of histological images. Accurate results of cell nuclei segmentation are often adapted to a variety of applications such as the detection of cancerous cell nuclei and the observation of overlapping cellular events occurring during wound healing process in the human body. In this paper, an automated...

The main objective of this project is cell nuclei segmentation and classification. In pre-processing convert the gray scale and apply the segmentation. In segmentation this project proposes the graph cut algorithm. After segmentation the features are extracts such as texture and etc. In classification this project used the feed forward neural network. The proposed method is very efficient. The ...

This dissertation presents contributions to the automation of cell image analysis, in particular the segmentation of fluorescent nuclei and probes, and the evaluation of segmentation results. We present two new methods of segmentation of nuclei and chromosomal probes – core objects for cytometry medical imaging. Our nucleic segmentation method is mathematically grounded on a novel parametric mo...