An information-theoretic detector based scheme for registration of speckled medical images

Several studies dealt with medical ultrasound registration. Their similarity metrics relied on pixel-to-pixel intensity comparisons. Hence, they are not well suited to the case of speckled images. To better handle the speckle noise, our previous work proposed an information-theoretic feature detector-based registration approach. This work aims to extend it to the cases where the image speckle model is Rayleigh or normalized Fisher-Tippett distributed. Using speckle modeling based on these distributions, a speckle-specific information- theoretic feature detector is constructed and applied to provide feature images. Those feature images are then registered using differential equations, the solution of which provides a transformation to bring the images into alignment. Compared to standard gradient-based techniques, the experimental results demonstrate the effectiveness of our method, particularly for low contrast ultrasound images

Registration of Ultrasound Images Using an Information-Theoretic Feature Detector

In this paper, we present a new method for ultrasound image registration. For each image to be registered, our method first applies an ultrasound-specific information-theoretic feature detector, which is based on statistical modeling of speckle and provides a feature image that robustly delineates important edges in the image. These feature images are then registered using differential equations, the solution of which provides a locally optimal transformation that brings the images into alignment. We describe our method and present experimental results demonstrating its effectiveness, particularly for low contrast, speckled images. Furthermore, we compare our method to standard gradient-based techniques, which we show are more susceptible to misregistration

Enhanced phase congruency feature-based image registration for multimodal remote sensing imagery

Multimodal image registration is an essential image processing task in remote sensing. Basically, multimodal image registration searches for optimal alignment between images captured by different sensors for the same scene to provide better visualization and more informative images. Manual image registration is a tedious task and requires more effort, hence developing an automated image registration is very crucial to provide a faster and reliable solution. However, image registration faces many challenges from the nature of remote sensing image, the environment, and the technical shortcoming of the current methods that cause three issues, namely intensive processing power, local intensity variation, and rotational distortion. Since not all image details are significant, relying on the salient features will be more efficient in terms of processing power. Thus, the feature-based registration method was adopted as an efficient method to avoid intensive processing. The proposed method resolves rotation distortion issue using Oriented FAST and Rotated BRIEF (ORB) to produce invariant rotation features. However, since it is not intensity invariant, it cannot support multimodal data. To overcome the intensity variations issue, Phase Congruence (PC) was integrated with ORB to introduce ORB-PC feature extraction to generate feature invariance to rotation distortion and local intensity variation. However, the solution is not complete since the ORB-PC matching rate is below the expectation. Enhanced ORB-PC was proposed to solve the matching issue by modifying the feature descriptor. While better feature matches were achieved, a high number of outliers from multimodal data makes the common outlier removal methods unsuccessful. Therefore, the Normalized Barycentric Coordinate System (NBCS) outlier removal was utilized to find precise matches even with a high number of outliers. The experiments were conducted to verify the registration qualitatively and quantitatively. The qualitative experiment shows the proposed method has a broader and better features distribution, while the quantitative evaluation indicates improved performance in terms of registration accuracy by 18% compared to the related works

A Method for Predicting Dose Changes for HN Treatment Using Surface Imaging

Head and neck cancer is commonly treated with a six- to seven-week course of radiotherapy, during which a patient’s anatomy may change substantially, due to target reduction or weight loss. Anatomical changes lead to reduction in treatment quality due to decreased setup reproducibility and altered dose deposition compared to the original plan. Few clinics have developed a standard method for triggering resimulation and replan due to anatomic changes. This work investigates a new method for determining when to resimulate and replan HNC patients by utilizing their topographic anatomical changes to predict differences in planned versus delivered dose distributions. The first part of the work presents a method for deformable image registration of CT to CBCT which addresses the challenges of inaccurate Hounsfield units and truncated field of view present in CBCT. The registration method was validated on 10 HN patients using contour comparison, with average DSC of 0.82, 0.74, 0.72, and 0.69 for mandible, cord, and left and right parotid. The registration method was then used to generate dose maps and surface contours for 47 patients for the second part of this work, the development of a U-Net which takes the original dose distribution, the original surface, and the treatment day surface as input and predicts the treatment day dose distribution as output. The average RMSE and MAE between the true and predicted dose distributions for a test set of 6 patients was 4.25 and 2.15. This work proves feasibility of a dose prediction neural network using surface imaging

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

Fast 4D Ultrasound Registration for Image Guided Liver Interventions

Liver problems are a serious health issue. The common liver problems are hepatitis, fatty liver, liver cancer and liver damage caused by alcohol abuse. Continuous, long term disease may cause a condition of the liver known as the Liver Cirrhosis. Liver cirrhosis makes the liver scarred and hardened up causing portal hypertension. In such a situation the collateral vessels try to bypass the liver as blood cannot freely flow through the liver; causing internal bleeding. One of the treatments of portal hypertension is Transjugular intrahepatic portosystemic shunt (TIPS). In a TIPS procedure a tract in the liver is created that shortcuts two veins in the liver, reducing the portal hypertension. Radiofrequency ablation (RFA) is use for the treatment of liver cancer. In RFA, a needle electrode is placed through the skin into the liver tumor. High-frequency electrical currents are passed through the electrode, creating heat that destroys the cancer cells, without damaging the surrounding liver tissues. TIPS and RFA are minimally invasive procedures, where small incisions are made to perform the surgery and are alternative to open surgery. A minimally invasive alternative has large potential in reducing complication rates, minimizing surgical trauma and reducing hospital stay. However, in these procedures, due to lack of direct eyesight, three-dimensional imaging information about the anatomy and instruments during the intervention is required. The most difficult part of these procedures is the interpretation and selection of oblique views for needle/instrument insertion and target visualization. In our work we develop and evaluate techniques that enable the effective use of 3D ultrasound for image guided interventions. Ultrasound is low cost, mobile and unlike CT and X-rays does not use any harmful radiation in the imaging process. During these procedures, breathing shifts the region of interest and makes it difficult to constantly focus on a region of interest. We provide an approach to correct for the motion due to breathing. Additionally, we propose a method for image fusion of interventional ultrasound and preoperative imaging modalities such as CT for cases where the lesions are visible in CT but not visible in ultrasound. Incorporating CT data during intervention additionally adds greater definition and precision to the ultrasound based navigation system. Concluding, in this thesis, we presented methods and evaluated their accuracies that demonstrate the use of real-time 3D US and its fusion with CT in potentially improving image guidance in minimally invasive US guided liver interventions

Image analysis tool for the characterisation of bone turnover in the appendicular skeleton

Osteoporosis is a disease characterised by reduced bone mass and altered microarchitecture leading to an increased risk of fracture. The consequences of osteoporosis include reduced quality of life and pain, associated with fractures. Its financial burden on health services are significant. Characterisation of osteoporosis using imaging techniques is therefore important. Peripheral Quantitative Computed Tomography (pQCT) is a cross-sectional imaging method which is used to scan bones in the appendicular skeleton. pQCT imaging may be particularly useful in clinical groups where changes in bone mineral density (BMD) and structure are known to occur in the limbs. Two such groups are patients following spinal cord injury (SCI) or anterior cruciate ligament (ACL) injury. Aims. This project aimed to develop analysis techniques to characterise bone in pQCT images. Their purpose was to describe localised changes within pQCT images of the bone, as opposed to the standard global measurements. Methods. Fully automated segmentation and registration software was developed and tested followed by two independent processing algorithms. The first generates spatial maps to characterise local changes in BMD. This is achieved using both quadrant analysis software and a voxel-based approach, the latter comparing pairs of images and generating a voxel-by-voxel ΔBMD map of changes in BMD. The second processing algorithm uses morphological granulometries to investigate the bone microarchitecture. Results. Evaluation of these image analysis methods was carried out using two clinical studies. The first investigates acute longitudinal changes in the distal tibia (DT) and distal femur (DF) post-motor-complete-SCI using pQCT. Images from 15 subjects (13M, 2F) with a mean age of 36y±19y, were acquired at 4-monthly intervals during the first year post-injury. The second comprises of ACL injury subjects, with imaging of the injured and contralateral proximal tibia (PT) and distal femur before (n=19, 18M 1F, 30y±9y of age) and after (n=8, 8M 0F, 31y±9y of age) surgical ACL reconstruction. The software developed to automatically segment bone from surrounding structures was successful: 98% success rate for epiphyseal tibial regions, 67% success rate for the distal femur. Registration of images was then performed and the spatial analysis methods to automatically produce quadrants of trabecular bone were applied, displaying individual results graphically. The voxel based analysis method was developed, tested and applied to produce ΔBMD maps, utilising statistical inference and corrections for multiple comparisons using a false-discovery rate technique. These maps characterised localised changes in BMD between pairs of both longitudinal and contralateral images. Software was also developed to apply morphological granulometries to pQCT images, calculating global and local pattern spectrum moments. On application of the analysis methods to the longitudinal SCI images, the BMD and microarchitecture findings were observed to be disparate amongst subjects, with large variations in bone characteristics both globally and regionally. The quadrant and voxel based analysis methods provided information on longitudinal regional changes in each subject, indicating individual patterns of change. Structural analysis of bone microarchitecture using granulometries was demonstrated to have potential as a useful adjunct to BMD in identifying SCI subjects more susceptible to rapid bone loss. The analysis methods were also successfully applied to the ACL injury subjects. Following segmentation and registration, the total and trabecular BMD in the injured knee was observed to be significantly lower than that of the contralateral control knee pre-operatively for both the PT and DF (p<0.05). Post-operatively the total and trabecular BMD in the injured DF remained significantly low (p<0.05), however the PT demonstrated significantly lower BMD in the injured leg for the trabecular bone only (p<0.05). Reduced BMD in the PT post-operatively in humans is a novel observation, and indicates a benefit afforded by segmenting trabecular from cortical bone. Regional analysis using quadrants indicated some anatomical variation in bone loss within the injured limb, although it is acknowledged that these are preliminary findings which would require to be confirmed in larger studies. The voxel ΔBMD maps generally indicated global losses across the bones of the ACL injured leg both pre-operatively and post-operatively. No consistent patterns were obtained in the ΔBMD maps for these subjects, suggesting individual patterns of response to ACL injury. The structural information provided by granulometric analysis was limited for the ACL study. Conclusions. Automated software has been developed to characterise bone in pQCT images of the appendicular skeleton. It has been successfully applied to two clinical studies, facilitating localised changes in bone density to be demonstrated and descriptions of microarchitecture to be provided. The SCI subjects appear to have individualistic responses to injury, with a wide range of changes in bone density and microarchitecture observed. ACL injury patients all lost bone mass, but patterns of change were variable. The analysis methods developed to permit characterisation of bones in individual subjects, are proposed to be of value in both clinical and research domains exploring bone mass and microarchitecture, with the ultimate goals being the prediction of fracture risk and tailoring therapy for the individual