Automatic liver vessel segmentation using 3D region growing and hybrid active contour model

This paper proposes a new automatic method for liver vessel segmentation by exploiting intensity and shape constraints of 3D vessels. The core of the proposed method is to apply two different strategies: 3D region growing facilitated by bi-Gaussian filter for thin vessel segmentation, and hybrid active contour model combined with K-means clustering for thick vessel segmentation. They are then integrated to generate final segmentation results. The proposed method is validated on abdominal computed tomography angiography (CTA) images, and obtains an average accuracy, sensitivity, specificity, Dice, Jaccard, and RMSD of 98.2%, 68.3%, 99.2%, 73.0%, 66.1%, and 2.56 mm, respectively. Experimental results show that our method is capable of segmenting complex liver vessels with more continuous and complete thin vessel details, and outperforms several existing 3D vessel segmentation algorithms

Synchrotron-based visualization and segmentation of elastic lamellae in the mouse carotid artery during quasi-static pressure inflation

This dataset contains images that were obtained during quasi-static pressure inflation of mouse carotid arteries. Images were taken with phase propagation imaging at the X02DA TOMCAT beamline of the Swiss Light Source synchrotron at the Paul Scherrer Institute in Villigen, Switzerland. Scans of n=12 left carotid arteries (n-6 Apoe-deficient mice, n=6 wild-type mice, all on a C57Bl6J background) were taken at pressure levels of 0, 10, 20, 30, 40, 50, 70, 90 and 120 mmHg. For analysis we selected 75 images from the center of each stack (starting at the center of the stack, and skipping 2 of every three images in both cranial and caudal axial directions) for each sample and for each pressure level, resulting in a total of 75 x 12 x 9 = 8100 analyzed images from 108 different scans. Segmentation, 3D visualization and geometric analysis is presented in the corresponding manuscript. Files are uploaded in 16bit .tif format and are named: mouseid_pressurelevel_stacknumber, with mouseid consisting of either Apoe (Apoe-deficient) or Bl (wild-type) and the mouse number, pressurelevel varies from P0 to P120 and stacknumber indicates which image from the stack has been uploaded

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.Rudyanto, RD.; Kerkstra, S.; Van Rikxoort, EM.; Fetita, C.; Brillet, P.; Lefevre, C.; Xue, W.... (2014). Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study. Medical Image Analysis. 18(7):1217-1232. doi:10.1016/j.media.2014.07.003S1217123218

Contrast-enhanced micro-computed tomography and image processing integrated approach for microstructural analysis of biological soft fibrous tissues

Nel sistema muscolo-scheletrico, tendini e legamenti svolgono un ruolo importante al fine di garantire mobilità e stabilità. Questi tessuti sono composti principalmente da collagene e presentano una struttura altamente fibrosa. Evidenziare i componenti della microstruttura di legamenti e tendini in immagini tridimensionali (3D) è di fondamentale importanza per estrarre informazioni significative che posso anvere ripercussioni sulla scienza di base e sulle applicazioni ortopediche. In particolare, le proprietà meccaniche delle microstrutture fibrose sono fortemente influenzate da alcune caratteristiche geometriche, come la volume fraction, l’orientamento e il diametro; tuttavia, determinare l'orientamento e il diametro della fibra 3D è impegnativo. In questa prospettiva, questa tesi mirava ad unire tomografia microcomputerizzata (microCT) ed elaborazione delle immagini in un approccio integrato al fine di identificare e migliorare le informazioni microstrutturali sui tessuti biologici fibrosi, includendo i dati di volume e orientamento. La procedura complessiva è stata applicata per la prima volta su campioni di tendine del ginocchio umano e su legamento collaterale bovino. In una prima fase, sono state testate preparazioni specifiche del campione, inclusa una disidratazione chimica o soluzioni di acido fosfotungstico (PTA) al 2 % in acqua (H2O) o in soluzione di etanolo al 70% (EtOH), così da migliorare il contrasto dell'immagine di questi specifici tessuti. Inoltre, utilizzando i dati scansionati, è stata sviluppata una nuova tecnica di elaborazione delle immagini basata sul filtro 3D hessiano multiscala per evidenziare le strutture fibrose ed ottenere informazioni quantitative sulle fibre. È interessante notare che, per qualsiasi strategia di preparazione del campione di tendini/legamenti, l'approccio proposto è risultato adeguato per rilevare e caratterizzare le proprietà del fascicolo. I risultati del test hanno mostrato che la disposizione delle fibre è fortemente allineata lungo la direzione longitudinale principale nel tendine del tendine, più delle fibre del legamento collaterale bovino. Inoltre, questa tecnica è stata ulteriormente applicata al fine di determinare come il Legamento Crociato Anteriore (LCA) umano risponda a carichi uniassiali rispetto a valori crescenti di deformazione, considerando sia un tessuto sano che uno in condizioni patologiche, cioè acquisito da un paziente con l'artrosi. Anche in questi casi, l'approccio integrato si è rivelato valido ed affidabile nell'individuare orientamento e dimensione dei fascicoli presenti e, quindi, attraverso un modello meccanico strutturale - basato su specifiche leggi costitutive - nello stimare il modulo elastico di questi tessuti. Sono state infatti stimate le curve sforzo-deformazione, ottenendo un valore di modulo elastico di 60.8 MPa e 7.7 MPa rispettivamente per il LCA sano e patologico. In conclusione, è stato progettato e validato in via preliminare un nuovo protocollo microCT per il miglioramento del contrasto dedicato all'analisi microstrutturale dei tessuti molli biologici con caratteristiche fibrose. In una peculiare applicazione al LCA, le informazioni ottenute con il protocollo sono state utilizzate per implementare un modello meccanico dei tessuti fibrosi, stimando così il comportamento biomeccanico dei tessuti sani e patologici.ABSTRACT In the musculoskeletal system, tendons and ligaments play an important role in ensuring mobility and stability. These tissues are primarily composed of collagen and present a highly fibrous structure. Highlighting the microstructure components of ligaments and tendons in three-dimensional (3D) images is crucial for extracting meaningful information impacting basic science and orthopaedic applications. In particular, the mechanical properties of the fibrous microstructures are strongly influenced by their volume fraction, orientation, and diameter. However, determining the 3D fibre orientation and diameter is challenging. In this picture, this thesis aimed at integrating microcomputed tomography (microCT) and image processing approach to identify and enhance microstructural information about biological soft fibrous tissues, including volume and orientation. The overall procedure was first applied on human hamstring tendon and bovine collateral ligament samples. In a first phase specific sample preparations – including either a chemical dehydration, or by 2% of phosphotungstic acid (PTA) in water (H2O) or in 70% ethanol (EtOH) solution – were tested to enhance image contrast of these specific soft tissues. Further, using the scanned data, a novel image processing technique based on 3D Hessian multiscale filter for highlighting fibrous structures was developed to obtain quantitative fibre information. Interestingly, for any strategy of tendon/ligament sample preparation, the proposed approach was adequate for detecting and characterizing fascicle features. The test results showed the fibre arrangement strongly aligned along the main longitudinal direction in the human hamstring tendon more than fibres on the bovine collateral ligament. Moreover, this technique was further applied in order to determine how the human Anterior Cruciate Ligament (ACL) responds to uniaxial loads with respect to increasing values of strain, considering both a healthy tissue and a one under pathological conditions, i.e., acquired from a patient with osteoarthritis. Also in these cases, the integrated approach was valuable and reliable in identifying orientation and size of present fascicles and, thus, through a structural mechanical model - based on specific constitutive law - to estimate the elastic modulus of these tissues. In fact, stress-strain curves were estimated, obtaining a value of elastic modulus of 60.8 MPa and 7.7 MPa for the healthy and pathological ACLs, respectively. In conclusion, a novel contrast enhancement microCT protocol was designed and preliminarily validated for the microstructural analysis of biological soft fibrous tissues. In a peculiar application to ACL, the information obtained with the protocol was used to implement a mechanical model of fibrous tissues, thus estimating the biomechanical behaviour of the healthy and pathological tissues

New Image Processing Methods for Ultrasound Musculoskeletal Applications

In the past few years, ultrasound (US) imaging modalities have received increasing interest as diagnostic tools for orthopedic applications. The goal for many of these novel ultrasonic methods is to be able to create three-dimensional (3D) bone visualization non-invasively, safely and with high accuracy and spatial resolution. Availability of accurate bone segmentation and 3D reconstruction methods would help correctly interpreting complex bone morphology as well as facilitate quantitative analysis. However, in vivo ultrasound images of bones may have poor quality due to uncontrollable motion, high ultrasonic attenuation and the presence of imaging artifacts, which can affect the quality of the bone segmentation and reconstruction results. In this study, we investigate the use of novel ultrasonic processing methods that can significantly improve bone visualization, segmentation and 3D reconstruction in ultrasound volumetric data acquired in applications in vivo. Specifically, in this study, we investigate the use of new elastography-based, Doppler-based and statistical shape model-based methods that can be applied to ultrasound bone imaging applications with the overall major goal of obtaining fast yet accurate 3D bone reconstructions. This study is composed to three projects, which all have the potential to significantly contribute to this major goal. The first project deals with the fast and accurate implementation of correlation-based elastography and poroelastography techniques for real-time assessment of the mechanical properties of musculoskeletal tissues. The rationale behind this project is that, iii in the future, elastography-based features can be used to reduce false positives in ultrasonic bone segmentation methods based on the differences between the mechanical properties of soft tissues and the mechanical properties of hard tissues. In this study, a hybrid computation model is designed, implemented and tested to achieve real time performance without compromise in elastographic image quality . In the second project, a Power Doppler-based signal enhancement method is designed and tested with the intent of increasing the contrast between soft tissue and bone while suppressing the contrast between soft tissue and connective tissue, which is often a cause of false positives in ultrasonic bone segmentation problems. Both in-vitro and in-vivo experiments are performed to statistically analyze the performance of this method. In the third project, a statistical shape model based bone surface segmentation method is proposed and investigated. This method uses statistical models to determine if a curve detected in a segmented ultrasound image belongs to a bone surface or not. Both in-vitro and in-vivo experiments are performed to statistically analyze the performance of this method. I conclude this Dissertation with a discussion on possible future work in the field of ultrasound bone imaging and assessment

Echocardiography

The book "Echocardiography - New Techniques" brings worldwide contributions from highly acclaimed clinical and imaging science investigators, and representatives from academic medical centers. Each chapter is designed and written to be accessible to those with a basic knowledge of echocardiography. Additionally, the chapters are meant to be stimulating and educational to the experts and investigators in the field of echocardiography. This book is aimed primarily at cardiology fellows on their basic echocardiography rotation, fellows in general internal medicine, radiology and emergency medicine, and experts in the arena of echocardiography. Over the last few decades, the rate of technological advancements has developed dramatically, resulting in new techniques and improved echocardiographic imaging. The authors of this book focused on presenting the most advanced techniques useful in today's research and in daily clinical practice. These advanced techniques are utilized in the detection of different cardiac pathologies in patients, in contributing to their clinical decision, as well as follow-up and outcome predictions. In addition to the advanced techniques covered, this book expounds upon several special pathologies with respect to the functions of echocardiography

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book