Informatics opportunities and challenges in medical imaging : a journey

The role of the field of informatics in medical imaging is vital; novel or adapted informatics’ core methods can be employed to realise innovative information processing and engineering of medical images. As such, imaging informatics can assist in the interpretation of image-based, clinically recorded evidence. This, in turn, leads to the generation of associated actionable knowledge to achieve precision medicine practice. The discipline of informatics has the power to transform data to useful clinical information patterns of observable evidence and, subsequently to generate actionable knowledge in terms of diagnosis, prognosis, and disease management. This paper presents the author’s personal viewpoint and distinct contributions to innovations in the acquisition and collection of imaging data; storage, retrieval, and management of imaging information objects; quantitative analysis, classification, and dissemination of imaging observable evidence

The quest for "diagnostically lossless" medical image compression using objective image quality measures

Given the explosive growth of digital image data being generated, medical communities worldwide have recognized the need for increasingly efficient methods of storage, display and transmission of medical images. For this reason lossy image compression is inevitable. Furthermore, it is absolutely essential to be able to determine the degree to which a medical image can be compressed before its “diagnostic quality” is compromised. This work aims to achieve “diagnostically lossless compression”, i.e., compression with no loss in visual quality nor diagnostic accuracy. Recent research by Koff et al. has shown that at higher compression levels lossy JPEG is more effective than JPEG2000 in some cases of brain and abdominal CT images. We have investigated the effects of the sharp skull edges in CT neuro images on JPEG and JPEG 2000 lossy compression. We provide an explanation why JPEG performs better than JPEG2000 for certain types of CT images. Another aspect of this study is primarily concerned with improved methods of assessing the diagnostic quality of compressed medical images. In this study, we have compared the performances of structural similarity (SSIM) index, mean squared error (MSE), compression ratio and JPEG quality factor, based on the data collected in a subjective experiment involving radiologists. An receiver operating characteristic (ROC) curve and Kolmogorov-Smirnov analyses indicate that compression ratio is not always a good indicator of visual quality. Moreover, SSIM demonstrates the best performance. We have also shown that a weighted Youden index can provide SSIM and MSE thresholds for acceptable compression. We have also proposed two approaches of modifying L2-based approximations so that they conform to Weber’s model of perception. We show that the imposition of a condition of perceptual invariance in greyscale space according to Weber’s model leads to the unique (unnormalized) measure with density function ρ(t) = 1/t. This result implies that the logarithmic L1 distance is the most natural “Weberized” image metric. We provide numerical implementations of the intensity-weighted approximation methods for natural and medical images

Enhancing a Neurosurgical Imaging System with a PC-based Video Processing Solution

This work presents a PC-based prototype video processing application developed to be used with a specific neurosurgical imaging device, the OPMI® PenteroTM operating microscope, in the Department of Neurosurgery of Helsinki University Central Hospital at Töölö, Helsinki. The motivation for implementing the software was the lack of some clinically important features in the imaging system provided by the microscope. The imaging system is used as an online diagnostic aid during surgery. The microscope has two internal video cameras; one for regular white light imaging and one for near-infrared fluorescence imaging, used for indocyanine green videoangiography. The footage of the microscope’s current imaging mode is accessed via the composite auxiliary output of the device. The microscope also has an external high resolution white light video camera, accessed via a composite output of a separate video hub. The PC was chosen as the video processing platform for its unparalleled combination of prototyping and high-throughput video processing capabilities. A thorough analysis of the platform and efficient video processing methods was conducted in the thesis and the results were used in the design of the imaging station. The features found feasible during the project were incorporated into a video processing application running on a GNU/Linux distribution Ubuntu. The clinical usefulness of the implemented features was ensured beforehand by consulting the neurosurgeons using the original system. The most significant shortcomings of the original imaging system were mended in this work. The key features of the developed application include: live streaming, simultaneous streaming and recording, and playing back of upto two video streams. The playback mode provides full media player controls, with a frame-by-frame precision rewinding, in an intuitive and responsive interface. A single view and a side-by-side comparison mode are provided for the streams. The former gives more detail, while the latter can be used, for example, for before-after and anatomic-angiographic comparisons.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Medical image enhancement

Each image acquired from a medical imaging system is often part of a two-dimensional (2-D) image set whose total presents a three-dimensional (3-D) object for diagnosis. Unfortunately, sometimes these images are of poor quality. These distortions cause an inadequate object-of-interest presentation, which can result in inaccurate image analysis. Blurring is considered a serious problem. Therefore, “deblurring” an image to obtain better quality is an important issue in medical image processing. In our research, the image is initially decomposed. Contrast improvement is achieved by modifying the coefficients obtained from the decomposed image. Small coefficient values represent subtle details and are amplified to improve the visibility of the corresponding details. The stronger image density variations make a major contribution to the overall dynamic range, and have large coefficient values. These values can be reduced without much information loss

The Empirical Foundations of Teleradiology and Related Applications: A Review of the Evidence

Introduction: Radiology was founded on a technological discovery by Wilhelm Roentgen in 1895. Teleradiology also had its roots in technology dating back to 1947 with the successful transmission of radiographic images through telephone lines. Diagnostic radiology has become the eye of medicine in terms of diagnosing and treating injury and disease. This article documents the empirical foundations of teleradiology. Methods: A selective review of the credible literature during the past decade (2005?2015) was conducted, using robust research design and adequate sample size as criteria for inclusion. Findings: The evidence regarding feasibility of teleradiology and related information technology applications has been well documented for several decades. The majority of studies focused on intermediate outcomes, as indicated by comparability between teleradiology and conventional radiology. A consistent trend of concordance between the two modalities was observed in terms of diagnostic accuracy and reliability. Additional benefits include reductions in patient transfer, rehospitalization, and length of stay.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140295/1/tmj.2016.0149.pd

IMPROVED IMAGE QUALITY IN CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED INTERVENTIONS

In the past few decades, cone-beam computed tomography (CBCT) emerged as a rapidly developing imaging modality that provides single rotation 3D volumetric reconstruction with sub-millimeter spatial resolution. Compared to the conventional multi-detector CT (MDCT), CBCT exhibited a number of characteristics that are well suited to applications in image-guided interventions, including improved mechanical simplicity, higher portability, and lower cost. Although the current generation of CBCT has shown strong promise for high-resolution and high-contrast imaging (e.g., visualization of bone structures and surgical instrumentation), it is often believed that CBCT yields inferior contrast resolution compared to MDCT and is not suitable for soft-tissue imaging. Aiming at expanding the utility of CBCT in image-guided interventions, this dissertation concerns the development of advanced imaging systems and algorithms to tackle the challenges of soft-tissue contrast resolution. The presented material includes work encompassing: (i) a comprehensive simulation platform to generate realistic CBCT projections (e.g., as training data for deep learning approaches); (ii) a new projection domain statistical noise model to improve the noise-resolution tradeoff in model-based iterative reconstruction (MBIR); (iii) a novel method to avoid CBCT metal artifacts by optimization of the source-detector orbit; (iv) an integrated software pipeline to correct various forms of CBCT artifacts (i.e., lag, glare, scatter, beam hardening, patient motion, and truncation); (v) a new 3D reconstruction method that only reconstructs the difference image from the image prior for use in CBCT neuro-angiography; and (vi) a novel method for 3D image reconstruction (DL-Recon) that combines deep learning (DL)-based image synthesis network with physics-based models based on Bayesian estimation of the statical uncertainty of the neural network. Specific clinical challenges were investigated in monitoring patients in the neurological critical care unit (NCCU) and advancing intraoperative soft-tissue imaging capability in image-guided spinal and intracranial neurosurgery. The results show that the methods proposed in this work substantially improved soft-tissue contrast in CBCT. The thesis demonstrates that advanced imaging approaches based on accurate system models, novel artifact reduction methods, and emerging 3D image reconstruction algorithms can effectively tackle current challenges in soft-tissue contrast resolution and expand the application of CBCT in image-guided interventions

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

A cumulative index to the 1976 issues of a continuing bibliography on Aerospace Medicine and Biology

This publication is a cumulative index to the abstracts contained in Supplements 151 through 162 of Aerospace Medicine and Biology: A continuing bibliography. It includes three indexes - subject, personal author, and corporate source

Diseases of the Chest, Breast, Heart and Vessels 2019-2022

This open access book focuses on diagnostic and interventional imaging of the chest, breast, heart, and vessels. It consists of a remarkable collection of contributions authored by internationally respected experts, featuring the most recent diagnostic developments and technological advances with a highly didactical approach. The chapters are disease-oriented and cover all the relevant imaging modalities, including standard radiography, CT, nuclear medicine with PET, ultrasound and magnetic resonance imaging, as well as imaging-guided interventions. As such, it presents a comprehensive review of current knowledge on imaging of the heart and chest, as well as thoracic interventions and a selection of "hot topics". The book is intended for radiologists, however, it is also of interest to clinicians in oncology, cardiology, and pulmonology