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Dual-Rotation C-Arm Cone-Beam Tomographic Acquisition and Reconstruction Frameworks for Low-Contrast Detection in Brain Soft-Tissue Imaging Aymeric Reshef

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Dual-Rotation C-Arm Cone-Beam Tomographic Acquisition and Reconstruction Frameworks for Low-Contrast Detection in Brain Soft-Tissue Imaging Aymeric Reshef Dual-rotation C-arm cone-beam tomographic acquisition and reconstruction frameworks for low-contrast detection in brain soft-tissue imaging Aymeric Reshef To cite this version: Aymeric Reshef. Dual-rotation C-arm cone-beam tomographic acquisition and reconstruction frame- works for low-contrast detection in brain soft-tissue imaging. Medical Imaging. Télécom ParisTech, 2018. English. NNT : 2018ENST0044. tel-02077743v2 HAL Id: tel-02077743 https://hal.archives-ouvertes.fr/tel-02077743v2 Submitted on 27 Apr 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 2018-ENST-0044 EDITE - ED 130 Doctorat ParisTech THÈSE pour obtenir le grade de docteur délivré par TELECOM ParisTech Spécialité « Signal et Images » présentée et soutenue publiquement par Aymeric RESHEF le 25 septembre 2018 Dual-rotation C-arm cone-beam tomographic acquisition and reconstruction frameworks for low-contrast detection in brain soft-tissue imaging Directrice de thèse : Pr. Isabelle BLOCH Co-encadrement de la thèse : Saïd Ladjal, TELECOM ParisTech Cyril RIDDELL, GE Healthcare T Jury M. Emil SIDKY, Professeur, University of Chicago (USA) Rapporteur H M. Laurent DESBAT, Professeur, TIMC-IMAG, Université Grenobles-Alpes (La Tronche) Rapporteur Mme Irène BUVAT, Directeur de recherche, Laboratoire IMIV, Inserm/CEA (Orsay) Examinatrice È M. Dimitris VISVIKIS, Directeur de recherche, LaTIM, Inserm U1101 (Brest) Président du Jury S M. Saïd LADJAL, Maître de conférences, TELECOM ParisTech (Paris) Examinateur M. Cyril RIDDELL, Ingénieur de recherche, GE Healthcare (Buc) Examinateur E TELECOM ParisTech École de l’Institut Mines-Télécom - Membre de ParisTech 46 rue Barrault 75013 Paris - (+33) 1 45 81 77 77 - www.telecom-paristech.fr Et de l`asortant, nous revˆımes les ´etoiles. Dante, La Divine Com´edie On m’a dit qu’apr`es avoir r´edig´emon manuscrit de th`ese, le plus dur serait fait. C’est inexact. En r´ealit´e, le plus dur est de trouver la formule pour remercier tous ceux qui, de pr`es ou de loin, m’ont accompagn´ejusqu’ici. Une th`ese n’est rien sans son encadrement, et `ace titre je remercie les per- sonnes qui ont pris part `ace travail : Cyril, Yves, Sa¨ıd, Isabelle, cette exp´erience eˆut ´et´ebien diff´erente sans vous ! Je suis reconnaissant aux membres du jury d’avoir pris le temps de lire et de commenter mes travaux de recherche : merci donc `aDimitris Visvikis, Ir`ene Buvat, Laurent Desbat, et Emil Sidky, pour vos relectures bienveillantes. J’ai pass´ele plus clair de mon temps de travail `aGE Healthcare `aBuc. Je remercie l’´equipe qui m’a accueilli l`a-bas : Michel Grimaud a ´et´emon manager au d´ebut de ma th`ese, et je le remercie de m’avoir re¸cu dans son ´equipe. Val´erie Desnoux a ensuite ´et´emanager de cette ´equipe, et je la remercie de m’avoir gard´ejusqu’au bout de mon contrat ! Mes remerciements s’´etendent `al’ensemble des ing´enieurs permanents, consultants, doctorants, et stagiaires, qui ont partag´e mon quotidien. J’ai eu le bonheur de rejoindre une autre ´equipe juste apr`es mon contrat de th`ese, et c’est aupr`es d’elle que j’ai achev´ela r´edaction de ce manuscrit. Je remercie chaleureusement Didier Verot, ainsi que toute son ´equipe, pour m’avoir si bien accueilli dans cette ´equipe Qualit´eImage. Un grand merci aux amis de toujours, aux amis d’enfance, aux amis de lyc´ee : ne changez rien, j’ai encore besoin de vos grains de folie ! Un grand merci `a vous qui avez brouill´eles fronti`eres entre coll`egues et amis : sans vous, les “perfect weeks” n’existeraient pas, pas plus que mes exc`es de caf´eines r´esultant de nos pauses interminables mais (disons-le) salutaires ! Un merci immense ´egalement `a l’Atelier Vermeer, `atous les peintres formidables aupr`es de qui j’ai pu m’´evader pendant la th`ese. Quoi qu’on en dise, si cette th`ese est ´ecrite et soutenue au- jourd’hui, c’est en grande partie grˆace `avous. Des noms de professeurs traversent aussi mon esprit : professeurs de math´e- matiques, d’histoire, de grec ancien, et tant d’autres, soyez remerci´es ! Cette th`ese a b´en´efici´ed’un financement dans le cadre des bourses CIFRE. Si elle avait eu d’autres sponsors, nul doute que l’on aurait pu nommer : (i) l’Adada, pour tous ces afterworks pass´es l`a-bas, pour les Miam’s et les Ralph, pour la bonne ambiance qui y r`egne, et pour les bi`eres que l’on y boit ; (ii) le caf´eCaron (et avant lui, Selecta), sans qui toutes nos pauses au travail n’auraient pas pu avoir lieu. Enfin, et avant toute chose, un merci chaleureux `ama famille : ce travail lui est d´edi´e. Table of contents List of Figures vii List of Tables xi 1 Interventional neuroradiology: a clinical context 1 1.1 Pathologies and treatments ...................... 2 1.1.1 Restoring blood flow ...................... 2 1.1.1.1 Balloon angioplasty and stent ........... 2 1.1.1.2 Mechanical thrombectomy ............. 3 1.1.2 Aneurysm coiling ........................ 4 1.1.3 Embolization of arteriovenous malformation . 5 1.2 Enabling INR procedures with imaging ................ 6 1.2.1 Pre-operative imaging ..................... 6 1.2.2 Per-operative imaging: the INR suite ............. 9 1.2.2.1 2D imaging ...................... 10 1.2.2.2 3D imaging ...................... 11 1.3 Goal of this thesis ........................... 13 1.3.1 Contributions .......................... 13 1.3.2 Thesis outline .......................... 14 2 Imaging with C-arm systems 17 2.1 2D X-ray imaging ............................ 18 2.1.1 System description ....................... 18 2.1.2 X-ray production ........................ 21 2.1.2.1 Bremsstrahlung ................... 21 2.1.2.2 Characteristic radiations . 22 2.1.2.3 Off-focal radiation, collimation . 23 2.1.3 X-ray attenuation ....................... 24 2.1.3.1 Interactions with matter . 24 i Table of contents 2.1.3.2 Beer’s law ...................... 25 2.1.3.3 Intensities, dose ................... 25 2.1.3.4 Polychromaticity and beam hardening . 26 2.1.4 Image formation ........................ 28 2.1.4.1 Primary intensities, scattered intensities . 28 2.1.4.2 Flat-panel detector technology . 28 2.1.5 Real-time image guidance ................... 29 2.1.5.1 Imaging modes .................... 29 2.1.5.2 Field of view and binned modes . 30 2.1.5.3 Exposure management . 30 2.1.6 Artifacts ............................. 31 2.1.6.1 Scattered intensities . 31 2.1.6.2 Non-uniform pixel response . 32 2.2 3D X-ray imaging ............................ 33 2.2.1 Principles of circular computed tomography . 34 2.2.1.1 Geometries ...................... 34 2.2.1.2 Filtered backprojection . 38 2.2.1.3 Semi-discrete formulation . 39 2.2.1.4 Iterative reconstruction . 40 2.2.2 Image quality assessment ................... 42 2.2.2.1 The Catphanr 500 phantom . 42 2.2.2.2 Spatial resolution . 43 2.2.2.3 Contrast resolution . 43 2.2.3 Factors impacting low-contrast detection in C-arm CBCT . 45 2.2.3.1 Quantum noise .................... 45 2.2.3.2 Detector non-idealities . 45 2.2.3.3 X-ray beam ...................... 46 2.2.3.4 Scatter ........................ 47 2.2.3.5 Sampling ....................... 49 2.2.4 Discussion ............................ 50 3 Virtual bow-tie C-arm CBCT 53 3.1 A matter of noise ............................ 54 3.1.1 Impact of analog-to-digital conversion . 54 3.1.1.1 Principle of analog-to-digital conversion . 54 3.1.1.2 Ramp-based quantization . 55 3.1.1.3 Actual ramp-based ADC . 57 3.1.1.4 Quantization and low-contrast detection . 58 3.1.2 Influence of dose increase ................... 60 3.1.2.1 Experiments and results . 60 3.1.2.2 Conclusion ...................... 60 3.2 Virtual bow-tie via the dual-rotation framework . 62 3.2.1 Acquisition ........................... 62 3.2.1.1 Assumptions ..................... 62 3.2.1.2 Parameters ...................... 63 3.2.1.3 Virtual bow-tie .................... 64 ii Table of contents 3.2.2 Reconstruction ......................... 64 3.2.2.1 Analytical reconstruction . 64 3.2.2.2 Energy minimization . 65 3.2.2.3 Ramp filtering operators . 65 3.2.3 Experiments .......................... 66 3.2.3.1 Simulations ...................... 66 3.2.3.2 Acquisitions, reconstructions . 66 3.2.3.3 Image quality measures . 67 3.2.4 Results ............................. 69 3.2.4.1 Simulations ...................... 69 3.2.4.2 Real phantom data . 69 3.3 Discussion and conclusion ....................... 75 4 Direct reconstruction for virtual bow-tie C-arm CBCT 77 4.1 Filtered backprojection, backprojection-filtration . 78 4.1.1 Challenges of dual-rotation direct reconstruction . 78 4.1.2 Backprojection-filtration methods: a literature review . 78 4.2 K-pass Hilbert-transformed DBP (DBP-HT-K) . 80 4.2.1 Parallel-beam case ....................... 80 4.2.1.1 Notations ....................... 80 4.2.1.2 Angular splitting ................... 81 4.2.1.3 Differentiated backprojection . 84 4.2.2 Divergent-beam case ...................... 85 4.2.2.1 Resampling formula for the fan-beam case . 85 4.2.2.2 Semi-discrete fan-beam BPF formula . 86 4.2.2.3 Extension to C-arm CBCT .
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