Assessment of hydrocephalus in children based on digital image processing and analysis

Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal accumulation of cerebrospinal fluid within the ventricular system of the brain with its subsequent progression. One of the most important diagnostic methods of identifying hydrocephalus is Computer Tomography (CT). The enlarged ventricular system is clearly visible on CT scans. However, the assessment of the disease progress usually relies on the radiologist’s judgment and manual measurements, which are subjective, cumbersome and have limited accuracy. Therefore, this paper regards the problem of semi-automatic assessment of hydrocephalus using image processing and analysis algorithms. In particular, automated determination of popular indices of the disease progress is considered. Algorithms for the detection, semi-automatic segmentation and numerical description of the lesion are proposed. Specifically, the disease progress is determined using shape analysis algorithms. Numerical results provided by the introduced methods are presented and compared with those calculated manually by a radiologist and a trained operator. The comparison proves the correctness of the introduced approach

POPRAWA JAKOŚCI OBRAZÓW TOMOGRAFICZNYCH O NISKIEJ DAWCE PROMIENIOWANIA

In this paper the problem of enhancement of low-dose CT scans was considered. In particular, popular pre-processing algorithms (such as anisotropic diffusion filter, non-local means filter, mean-shift filter) were tested and analyzed. The assessment of image quality improvement was performed based on the artificially generated artifacts, similar to those appearing in low-dose CT scans . Their effectiveness was investigated using the image quality measures, such as the mean square error and the structural similarity index.W artykule rozważono problem poprawy jakości obrazów z tomografu komputerowego, uzyskanych z wykorzystaniem niskich dawek promieniowania. W szczególności, przetestowano popularne algorytmy przetwarzania wstępnego (m.in. algorytm filtracji anizotropowej, średnich nielokalnych, przesunięcia do średniej) oraz przeanalizowano skuteczność ich działania. Oceny jakości poprawy dokonano w oparciu o sztucznie wygenerowane zakłócenia, symulujące artefakty towarzyszące w obrazach TK niskim dawkom promieniowania. Do ilościowego porównania stopnia poprawy jakości wykorzystano takie miary, jak błąd średniokwadratowy oraz indeks strukturalnego podobieństwa

Image segmentation algorithms for diagnosis support of hydrocephalus in children

Tyt. z nagłówka.Bibliogr. s. 318-319.Artykuł prezentuje wyniki badań nad wykorzystaniem algorytmów segmentacji obrazu na potrzeby wspomagania diagnostyki wodogłowia u dzieci. Prezentowana praca miała na celu porównanie efektywności wybranych metod segmentacji obrazu, wykorzystanych w celu precyzyjnego wyodrębnienia obszaru wodogłowia od zdrowej części mózgu. Dokładna segmentacja obrazu zmiany chorobowej oraz całego mózgu jest niezwykle istotna w późniejszej analizie porównawczej właściwości tych obszarów (takich jak rozmiar czy objętość). Proponowane metody stanowią podstawę do dalszego rozwoju systemu automatycznego wykrywania i analizy wodogłowia. W niniejszym artykule opisano oraz przedstawiono rezultaty zastosowania proponowanych algorytmów na rzeczywistych danych obrazowych pochodzących z tomografu komputerowego.Paper presents the results of applying image segmentation algorithms for precise detection of hydrocephalus in children's brain. Presented research was aimed at the comparison of effectiveness of several segmentation methods used for this purpose. Extraction of the hydrocephalus along with the whole brain area in the CT image are important steps for further quantitative assessment of the disease. Precise segmentation of both brain and lesion areas is particularly important for the comparative analysis of their key characteristics (like size or volume). Proposed methods forms the basis for further development of the system for an automatic detection and analysis of hydrocephalus. Results of applying proposed algorithms to real CT data sets are presented and discussed.Dostępny również w formie drukowanej.SŁOWA KLUCZOWE: mózg, wodogłowie, TK, segmentacja. KEYWORDS: brain, hydrocephalus,CT segmentation

Assessment of hydrocephalus in children based on digital image processing and analysis

Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal accumulation of cerebrospinal fluid within the ventricular system of the brain with its subsequent progression. One of the most important diagnostic methods of identifying hydrocephalus is Computer Tomography (CT). The enlarged ventricular system is clearly visible on CT scans. However, the assessment of the disease progress usually relies on the radiologist’s judgment and manual measurements, which are subjective, cumbersome and have limited accuracy. Therefore, this paper regards the problem of semi-automatic assessment of hydrocephalus using image processing and analysis algorithms. In particular, automated determination of popular indices of the disease progress is considered. Algorithms for the detection, semi-automatic segmentation and numerical description of the lesion are proposed. Specifically, the disease progress is determined using shape analysis algorithms. Numerical results provided by the introduced methods are presented and compared with those calculated manually by a radiologist and a trained operator. The comparison proves the correctness of the introduced approach