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Wyszukujesz frazę "Dziekiewicz, Miroslaw" wg kryterium: Wszystkie pola


Wyświetlanie 1-15 z 15
Tytuł:
Morphological evaluation of the iliac and femoral arteries; possibilities and perspectives
Autorzy:
Dziekiewicz, Mirosław
Markiewicz, Tomasz
Kozłowski, Wojciech
Maruszyński, Marek
Powiązania:
https://bibliotekanauki.pl/articles/1395696.pdf
Data publikacji:
2014-01-01
Wydawca:
Index Copernicus International
Tematy:
atherosclerosis
femoral artery
iliac artery
endovascular intervention
computed tomography
image analysis
Opis:
The study presented an approach to the morphometric image of atherosclerotic lesions of the final segment of the abdominal aorta, femoral and iliac arteries, considering possible endovascular intervention. The evaluation of these arteries is very important, because they are often used as a point of access for endovascular procedures performed on the peripheral arteries, or within the thoracic and abdominal aorta and its branches, as well as coronary arteries. The aim of the study was to determine morphometric measurements describing the atherosclerotic lesions, including the methodology of their surgical interpretation. Material and methods. The study group comprised 128 tomograms of patients qualified for surgery. An algorithm based on the mathematical morphology was designed to track the vessels, starting from the division of the common femoral artery, and ending at the bifurcation of the abdominal aorta. We proposed a set of numerical measurements of the observed arterial changes. Results and conclusions. We analysed 128 tomograms with a 94.5% efficiency, and with the assessment accuracy of the degree of lumen reduction (MAE- 1.5%). We observed much higher measurement values of local tortuosity of the atherosclerotic arteries (0.3 - 1 radians), as compared to their anatomical course in a healthy subject (0 - 0.2 radians). The presented method can be a very accurate and useful tool in the numerical analysis of the lumen distribution of the arteries and atherosclerosis, dedicated to surgeons elaborating management strategies.
Źródło:
Polish Journal of Surgery; 2014, 86, 1; 1-6
0032-373X
2299-2847
Pojawia się w:
Polish Journal of Surgery
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-feature ensemble system in the renal tumour classification task
Autorzy:
Osowska-Kurczab, Aleksandra Maria
Markiewicz, Tomasz
Dziekiewicz, Miroslaw
Lorent, Malgorzata
Powiązania:
https://bibliotekanauki.pl/articles/2128157.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
medical imaging
renal cell carcinoma
convolutional neural networks
textural features
support vector machine
computer vision
deep learning
technika deep learning
obrazowanie medyczne
rak nerkowokomórkowy
konwolucyjne sieci neuronowe
cechy tekstury
maszyna wektorów nośnych
wizja komputerowa
głęboka nauka
Opis:
Recently, the analysis of medical imaging is gaining substantial research interest, due to advancements in the computer vision field. Automation of medical image analysis can significantly improve the diagnosis process and lead to better prioritization of patients waiting for medical consultation. This research is dedicated to building a multi-feature ensemble model which associates two independent methods of image description: textural features and deep learning. Different algorithms of classification were applied to single-phase computed tomography images containing 8 subtypes of renal neoplastic lesions. The final ensemble includes a textural description combined with a support vector machine and various configurations of Convolutional Neural Networks. Results of experimental tests have proved that such a model can achieve 93.6% of weighted F1-score (tested in 10-fold cross validation mode). Improvement of performance of the best individual predictor totalled 3.5 percentage points.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e136749, 1--8
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-feature ensemble system in the renal tumour classification task
Autorzy:
Osowska-Kurczab, Aleksandra Maria
Markiewicz, Tomasz
Dziekiewicz, Miroslaw
Lorent, Malgorzata
Powiązania:
https://bibliotekanauki.pl/articles/2173572.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
medical imaging
renal cell carcinoma
convolutional neural networks
textural features
support vector machine
computer vision
deep learning
technika deep learning
obrazowanie medyczne
rak nerkowokomórkowy
konwolucyjne sieci neuronowe
cechy tekstury
maszyna wektorów nośnych
wizja komputerowa
głęboka nauka
Opis:
Recently, the analysis of medical imaging is gaining substantial research interest, due to advancements in the computer vision field. Automation of medical image analysis can significantly improve the diagnosis process and lead to better prioritization of patients waiting for medical consultation. This research is dedicated to building a multi-feature ensemble model which associates two independent methods of image description: textural features and deep learning. Different algorithms of classification were applied to single-phase computed tomography images containing 8 subtypes of renal neoplastic lesions. The final ensemble includes a textural description combined with a support vector machine and various configurations of Convolutional Neural Networks. Results of experimental tests have proved that such a model can achieve 93.6% of weighted F1-score (tested in 10-fold cross validation mode). Improvement of performance of the best individual predictor totalled 3.5 percentage points.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e136749
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-15 z 15

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