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Računalniško podprta zaznava in kvantifikacija intrakranialnih anevrizem
JERMAN, TIM (Avtor), Pernuš, Franjo (Mentor) Več o mentorju... Povezava se odpre v novem oknu

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Izvleček
Srčnožilne bolezni (SŽB) so vodilni vzrok smrti in invalidnosti na svetu. Zaradi demografskih sprememb, kot sta rast in staranje prebivalstva, pa se je pojavnost SŽB v zadnjih desetletjih še povečala. Srčnožilne bolezni najbolj prizadenejo srčni ter možganski žilji in povzročijo približno 32% vseh smrti na svetu. Zaradi neposrednega stroška zdravljenja bolezni in posredno izgubljenega denarja zaradi izpada oz. zmanjšanja bolnikove produktivnosti, so SŽB v veliko finančno breme svetovni ekonomiji. Zato je veliko povpraševanja po neprestanih izboljšavah pripomočkov in postopkov za zgodnje diagnosticiranje in učinkovito zdravljenje žilnih patologij. Pomembno vlogo pri zaznavi, načrtovanju in zdravljenju patologij ima medicinsko slikanje, ki ga je mogoče izboljšati z napredkom v zajemu slike ali tehnikah analize medicinskih slik. Med bolj razširjenimi možganskožilnimi patologijami so intrakranialne hladne sakularne anevrizme, ki nastanejo z napihovanjem oslabljenega predela žilja v mehurčkasto strukturo. Intrakranialne anevrizme, ki se pojavljajo v 1% do 5% svetovne populacije lahko v primeru rupture privedejo do hudih komplikacij. Čeprav je ruptura anevrizem redek pojav, so rupturirane anevrizme najbolj pogost vzrok (85%) za subarahnoidno krvavitev, ki privede do kapi. Da bi zmanjšali število oseb, ki doživijo subarahnoidno krvavitev, je potrebna zgodnja zaznava, prepoznava tistih anevrizem, ki so nagnjene h krvavitvam in njihovo zdravljenje. V trenutni klinični uporabi zaznavo in presojo anevrizem izvaja nevroradiolog z vizualnim pregledom dvo dimenzionalne (2D) ali tri dimenzionalne (3D) angiografske slike. Ker je kakovost angiografskih slik odvisna od količine vbrizganega kontrastnega sredstva, ločljivosti, šuma ter rekonstrukcijskih artefaktov, anevrizme pa so večinoma obdane s kompleksnim žilnim omrežjem, sta zaznava in kvantifikacija anevrizem preko vizualnega pregleda angiografskih slik izjemno zahtevni. Hkrati pa je tudi za izkušenega nevroradiologa zanesljiva zaznava anevrizem z vizualnim in interaktivnim pregledom surovih 3D slik časovno zelo potratna. Težavna je tudi kvantitativna ocena tveganja žilne patologije, ki jo tipično lahko dobimo z merjenjem morfoloških mer anevrizme v 2D angiografskih slikah. Čeprav je te mere lažje izmeriti v 2D, je mogoče iste mere natančneje izmeriti tudi v 3D, kar pa je za človeka težje opravilo. Za povečanje natančnosti in zanesljivosti zaznave patoloških struktur v medicinskih slikah ter zmanjšanje časa potrebnega za pregled 3D slike, je bilo na področju analize medicinskih slik veliko napora vloženega v razvoj orodij za avtomatsko ali računalniško podprto (angl. computer-aided) zaznavo ali kvantifikacijo patologij. Cilj avtomatske zaznave je zaznava anevrizem neodvisno od nevroradiologa. Nasprotno je cilj sistemov za računalniško podprto zaznavo pohitritev in racionalizacija zaznave za učinkovitejšo in natančnejšo delo nevroradiologov. V doktorski disertaciji smo razvili in vrednotili izvirne postopke za računalniško podprto zaznavo in kvantifikacijo intrakranialnih sakularnih anevrizem v 3D angiografskih slikah, ki so bili načrtovani tako, da pomagajo nevroradiologom k hitrejši, natančnejši in zanesljivejši diagnozi ter zdravljenju anevrizem. Primarni namen predstavljenih metod zaznave je zagotavljanje visoke občutljivosti in nizke specifičnosti zaznave, kar je ključno za klinično uporabo, kjer lahko napačna odločitev negativno vpliva na pacientovo življenje. Cilj predlagane metode zaznave pa je zagotoviti natančne in zanesljive morfološke meritve, ki so neodvisne od velikosti in oblike anevrizem, in tako lahko omogočajo njihovo spremljanje skozi čas.

Jezik:Angleški jezik
Ključne besede:medicinske slike, tridimenzionalne slike, angiografija, analiza medicinskih slik, ožilje, anevrizma, računalniško podprta detekcija, računalniško podprta kvantifikacija, morfologija, ruptura
Vrsta gradiva:Doktorsko delo/naloga (mb31)
Organizacija:FE - Fakulteta za elektrotehniko
Leto izida:2017
Število ogledov:629
Število prenosov:265
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Sekundarni jezik

Jezik:Slovenski jezik
Naslov:Computer-aided detection and quantification of intracranial aneurysms
Izvleček:
Cardiovascular diseases (CVDs) are the leading cause of disability and mortality in the world, and their impact has been increasing in the past decades because of demographic trends such as population growth and ageing. Around 32% of all deaths are caused by CVDs, which mostly affiect the cardiac and cerebral vasculatures. Through the direct cost of the treatment of pathologies and the indirect money lost due to lack of patient productivity, vascular pathologies act as a large financial burden on the economy. Therefore, there is a huge demand for constant improvement of tools and methods for early diagnosis and effiective treatment of vascular pathologies.Due to the important role of imaging in diagnosis, planning and treatment of vascular pathologies, further improvements of these processes are immediately possible by advancing either the image acquisition or image analysis techniques. One of the most typical cerebrovascular pathologies related to CVDs are aneurysms, baloonlike structures that bulge from a weakened portion of a vessel. Intracranial aneurysms have a prevalence from 1% to 5% of the world’s population and lead in the event of rupture to stroke, a serious and life threatening condition. Although aneurysm rupture is a rather rare event, ruptured aneurysms are the most common cause (85%) of nontraumatic subarachnoid hemorrhages, which lead to stroke. To prevent such fatal events, either through preventive measures or by surgical treatment, intracranial aneurysms need to be detected and assessed as early as possible. In current clinical practice, a neuroradiologist detects and assesses aneurysms by visual inspection of a two-dimensional (2D) or three-dimensional (3D) angiographic image. Because angiographic acquisitions may diffier substantially in the level of contrast, resolution, noise and artifacts and because aneurysms are often surrounded by complex vascular networks and other structures, the detection based on visual inspection of angiographic images is clearly a difficult task. Moreover, to reliably detect all the aneurysms by interactive visual inspection of raw 3D images, even a trained neuroradiologist may require an excessive amount of time. Even more difficult is the quantitative assessment of vascular pathologies which typically is performed by measuring the aneurysm morphologic metrics in 2D angiographic images. While these measurements are rather simple to perform in 2D, the same metrics are essentially more accurate when measured in 3D, which, if done manually, is a much more challenging task. To improve the accuracy and reliability of detection and quantification of pathological structures in medical images, in general, and to reduce 3D image inspection and assessment times, substantial effiorts have been underway in the field of medical image analysis towards the development of tools for either automated or computer-aided pathology detection and quantification. While the aim of automated methods is a system completely independent of the neuroradiologist, the aim of computer-aided systems is to streamline tedious and time-consuming tasks so that the neuroradiologist is both effiective at image inspection and performs the detection and quantification accurately and reliably. This thesis concentrates on the development and validation of methods for computer-aided detection and quantification of intracranial saccular aneurysms in 3D angiographic images that are designed to assist a clinician towards a quicker and more reliable diagnosis and treatment of aneurysms. The main emphasis of the presented detection methods is the provision of high sensitivity and low specificity which is essential if to be used in clinical routine where an incorrect decision can adversely impact a patient’s life, whereas the design of the proposed quantification method aimed at producing accurate and robust morphologic measures that are unaffiected by aneurysms’ size and shape variations, and thus, providing a reliable mean for monitoring the state of the aneurysms through time.

Ključne besede:medical images, tridimensional images, medical image analysis, angiography, vessels, aneurysm, computer aided detection, computer aided quantification, morphology, rupture

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