Advanced H-1 Lung Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is one of the widely used medical imaging modality, since it can provide both structural and functional assessment in a single imaging session. However, two major challenges should be considered by using MRI for lung imaging. The first challenge is the intrinsic low SNR of H-1 lung MRI due to the low proton density as well as the fast decay of the lung parenchyma signal. And the second challenge is subject motion. To achieve high resolution structural image, MRI requires a long scan time, usually a few minutes or even longer, which make MRI sensitive to subject motion. To address the first challenge, ultra-short echo time (UTE) MRI sequence is used to capture the lung parenchyma signal before decay. As for subject motion, two major strategies are widely used. One strategy is fast breath-holding scan, the subjects are asked to hold their breaths for a short duration, and the fast 3D MR sequence would be used to acquire data within that duration. This dissertation proposes a new acquisition scheme based on the standard UTE sequence, which largely increases the encoding efficiency and improves the breath-holding scan images. The other is free breathing scan with motion correction. The subjects are allowed to breathe during the MR acquisition. After the acquisition, the motion corrupted data would go through the motion correction step to reconstruct the motion free images. In this dissertation, two novel motion corrected reconstruction strategies are proposed to incorporate the motion modeling and compensation into the reconstruction to get high SNR motion corrected 3D and 4D images. When translating the developed techniques to the clinical studies, specifically for pediatric and neonatal studies, more practical problems need to be considered, such as smaller but finer anatomy to image, the different respiratory patterns of the young subjects etc. This dissertation proposes a 5-minute free breathing UTE MRI strategy to achieve a 3D high resolution motion free lung image for pediatric and neonatal studies

Respiratory organ motion in interventional MRI : tracking, guiding and modeling

Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy. In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities. Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well. Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence

Spatiotemporal alignment of in utero BOLD-MRI series

Purpose: To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. Materials and Methods: The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. Results: The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01). Conclusion: The proposed approach to align MRI time series enables more accurate quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs.National Institutes of Health (NIH) . Grant Numbers: U01 HD087211 , R01 EB017337 Consejeria de Educacion, Juventud y Deporte de la Comunidad de Madrid (Spain) through the Madrid-MIT M+Vision Consortium

Pre-Trained Driving in Localized Surroundings with Semantic Radar Information and Machine Learning

Entlang der Signalverarbeitungskette von Radar Detektionen bis zur Fahrzeugansteuerung, diskutiert diese Arbeit eine semantischen Radar Segmentierung, einen darauf aufbauenden Radar SLAM, sowie eine im Verbund realisierte autonome Parkfunktion. Die Radarsegmentierung der (statischen) Umgebung wird durch ein Radar-spezifisches neuronales Netzwerk RadarNet erreicht. Diese Segmentierung ermöglicht die Entwicklung des semantischen Radar Graph-SLAM SERALOC. Auf der Grundlage der semantischen Radar SLAM Karte wird eine beispielhafte autonome Parkfunktionalität in einem realen Versuchsträger umgesetzt. Entlang eines aufgezeichneten Referenzfades parkt die Funktion ausschließlich auf Basis der Radar Wahrnehmung mit bisher unerreichter Positioniergenauigkeit. Im ersten Schritt wird ein Datensatz von 8.2 · 10^6 punktweise semantisch gelabelten Radarpunktwolken über eine Strecke von 2507.35m generiert. Es sind keine vergleichbaren Datensätze dieser Annotationsebene und Radarspezifikation öffentlich verfügbar. Das überwachte Training der semantischen Segmentierung RadarNet erreicht 28.97% mIoU auf sechs Klassen. Außerdem wird ein automatisiertes Radar-Labeling-Framework SeRaLF vorgestellt, welches das Radarlabeling multimodal mittels Referenzkameras und LiDAR unterstützt. Für die kohärente Kartierung wird ein Radarsignal-Vorfilter auf der Grundlage einer Aktivierungskarte entworfen, welcher Rauschen und andere dynamische Mehrwegreflektionen unterdrückt. Ein speziell für Radar angepasstes Graph-SLAM-Frontend mit Radar-Odometrie Kanten zwischen Teil-Karten und semantisch separater NDT Registrierung setzt die vorgefilterten semantischen Radarscans zu einer konsistenten metrischen Karte zusammen. Die Kartierungsgenauigkeit und die Datenassoziation werden somit erhöht und der erste semantische Radar Graph-SLAM für beliebige statische Umgebungen realisiert. Integriert in ein reales Testfahrzeug, wird das Zusammenspiel der live RadarNet Segmentierung und des semantischen Radar Graph-SLAM anhand einer rein Radar-basierten autonomen Parkfunktionalität evaluiert. Im Durchschnitt über 42 autonome Parkmanöver (∅3.73 km/h) bei durchschnittlicher Manöverlänge von ∅172.75m wird ein Median absoluter Posenfehler von 0.235m und End-Posenfehler von 0.2443m erreicht, der vergleichbare Radar-Lokalisierungsergebnisse um ≈ 50% übertrifft. Die Kartengenauigkeit von veränderlichen, neukartierten Orten über eine Kartierungsdistanz von ∅165m ergibt eine ≈ 56%-ige Kartenkonsistenz bei einer Abweichung von ∅0.163m. Für das autonome Parken wurde ein gegebener Trajektorienplaner und Regleransatz verwendet

Real-Time Magnetic Resonance Imaging

Real‐time magnetic resonance imaging (RT‐MRI) allows for imaging dynamic processes as they occur, without relying on any repetition or synchronization. This is made possible by modern MRI technology such as fast‐switching gradients and parallel imaging. It is compatible with many (but not all) MRI sequences, including spoiled gradient echo, balanced steady‐state free precession, and single‐shot rapid acquisition with relaxation enhancement. RT‐MRI has earned an important role in both diagnostic imaging and image guidance of invasive procedures. Its unique diagnostic value is prominent in areas of the body that undergo substantial and often irregular motion, such as the heart, gastrointestinal system, upper airway vocal tract, and joints. Its value in interventional procedure guidance is prominent for procedures that require multiple forms of soft‐tissue contrast, as well as flow information. In this review, we discuss the history of RT‐MRI, fundamental tradeoffs, enabling technology, established applications, and current trends