Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: computer-aided diagnosis

Sortuj według:

Ogranicz wyniki do:

Nuclei segmentation for computer-aided diagnosis of breast cancer

100%

Kowal M., Filipczuk P.

International Journal of Applied Mathematics and Computer Science

2014

tom 24

nr 1

19-31

Breast cancer is the most common cancer among women. The effectiveness of treatment depends on early detection of the disease. Computer-aided diagnosis plays an increasingly important role in this field. Particularly, digital pathology has recently become of interest to a growing number of scientists. This work reports on advances in computer-aided breast cancer diagnosis based on the analysis of cytological images of fine needle biopsies. The task at hand is to classify those as either benign or malignant. We propose a robust segmentation procedure giving satisfactory nuclei separation even when they are densely clustered in the image. Firstly, we determine centers of the nuclei using conditional erosion. The erosion is performed on a binary mask obtained with the use of adaptive thresholding in grayscale and clustering in a color space. Then, we use the multi-label fast marching algorithm initialized with the centers to obtain the final segmentation. A set of 84 features extracted from the nuclei is used in the classification by three different classifiers. The approach was tested on 450 microscopic images of fine needle biopsies obtained from patients of the Regional Hospital in Zielona Góra, Poland. The classification accuracy presented in this paper reaches 100%, which shows that a medical decision support system based on our method would provide accurate diagnostic information.

Picture languages in automatic radiological palm interpretation

88%

Tadeusiewicz R., Ogiela M. R.

International Journal of Applied Mathematics and Computer Science

2005

tom 15

nr 2

305-312

The paper presents a new technique for cognitive analysis and recognition of pathological wrist bone lesions. This method uses AI techniques and mathematical linguistics allowing us to automatically evaluate the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm bones. This description was built with the use of graph linguistic formalisms already applied in artificial intelligence. The research described in this paper demonstrates that for the needs of palm bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well suited. Defining a graph image language adjusted to the specific features of the scientific problem described here permitted a semantic description of correct palm bone structures. It also enabled the interpretation of images showing some in-born lesions, such as additional bones or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.

Ograniczanie wyników

2 International Journal of Applied Mathematics and Computer Science

1 Filipczuk P.

1 Kowal M.

1 Ogiela M. R.

1 Tadeusiewicz R.

1 2014

1 2005

Wyniki wyszukiwania

Nuclei segmentation for computer-aided diagnosis of breast cancer

Picture languages in automatic radiological palm interpretation