Models of breast lesions based on three-dimensional X-ray breast images
| Autor: | Kristina Bliznakova, Zhivko Bliznakov, Giovanni Mettivier, Lesley Cockmartin, Ivan Buliev, Hilde Bosmans, Paolo Russo, Firgan Feradov, Nikolay Dukov |
|---|---|
| Přispěvatelé: | Dukov, Nikolay, Bliznakova, Kristina, Feradov, Firgan, Buliev, Ivan, Bosmans, Hilde, Mettivier, Giovanni, Russo, Paolo, Cockmartin, Lesley, Bliznakov, Zhivko |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Databases
Factual Computer science Software tool Normalization (image processing) General Physics and Astronomy 030218 nuclear medicine & medical imaging 0302 clinical medicine Segmentation Image noise reduction Whole Body Imaging Computational model Radiology Nuclear Medicine & Medical Imaging Breast lesions Dice similarity coefficients General Medicine SOFTWARE PHANTOM Tumor Burden Breast lesions Segmentation Breast tomosynthesis Dice similarity coefficients Region growing 030220 oncology & carcinogenesis SIMULATION medicine.symptom Life Sciences & Biomedicine Mammography Biophysics Breast Neoplasms Models Biological VALIDATION Lesion SYNCHROTRON-RADIATION 03 medical and health sciences MAMMOGRAPHY Imaging Three-Dimensional medicine Humans Computer Simulation Radiology Nuclear Medicine and imaging COMPUTED-TOMOGRAPHY ALGORITHM Science & Technology business.industry PLATFORM Pattern recognition Digital Breast Tomosynthesis PERFORMANCE Breast tomosynthesis Artificial intelligence business |
| Zdroj: | Physica Medica |
| Popis: | This paper presents a method for creation of computational models of breast lesions with irregular shapes from patient Digital Breast Tomosynthesis (DBT) images or breast cadavers and whole-body Computed Tomography (CT) images. The approach includes six basic steps: (a) normalization of the intensity of the tomographic images; (b) image noise reduction; (c) binarization of the lesion area, (d) application of morphological operations to further decrease the level of artefacts; (e) application of a region growing technique to segment the lesion; and (f) creation of a final 3D lesion model. The algorithm is semi-automatic as the initial selection of the region of the lesion and the seeds for the region growing are done interactively. A software tool, performing all of the required steps, was developed in MATLAB. The method was tested and evaluated by analysing anonymized sets of DBT patient images diagnosed with lesions. Experienced radiologists evaluated the segmentation of the tumours in the slices and the obtained 3D lesion shapes. They concluded for a quite satisfactory delineation of the lesions. In addition, for three DBT cases, a delineation of the tumours was performed independently by the radiologists. In all cases the abnormality volumes segmented by the proposed algorithm were smaller than those outlined by the experts. The calculated Dice similarity coefficients for algorithm-radiologist and radiologist-radiologist showed similar values. Another selected tumour case was introduced into a computational breast model to recursively assess the algorithm. The relative volume difference between the ground-truth tumour volume and the one obtained by applying the algorithm on the synthetic volume from the virtual DBT study is 5% which demonstrates the satisfactory performance of the proposed segmentation algorithm. The software tool we developed was used to create models of different breast abnormalities, which were then stored in a database for use by researchers working in this field. ispartof: PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS vol:57 pages:80-87 ispartof: location:Italy status: published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|