Multimodal and multiprotocol image registration refers to the process of alignment of two or more images obtained from different imaging modalities (e.g. digitized histology and MRI) and protocols (e.g. T2-w and PD-w MRI). Registration is a critical component in medical applications including image guided surgery, image fusion for cancer diagnosis and treatment planning, and automated tissue annotation. However, registration is often complicated on account of differences in both the image intensities and the shape of the underlying anatomy. For example, non-linear differences in the overall shape of the prostate between in vivo MRI and ex vivo whole mount histology (WMH) often exist as a result of the presence of an endorectal coil during pre-operative MR imaging and deformations to the specimen during slide preparation. To overcome these challenges, we present new registration techniques termed Combined Feature Ensemble Mutual Information (COFEMI) and Collection of Image-derived Non-linear Attributes for Registration Using Splines (COLLINARUS). The goal COFEMI is to provide a similarity measure that is driven by unique low level textural features, for registration that is more robust to intensity artifacts and modality differences than measures restricted to intensities alone. COLLINARUS offers the robustness of COFEMI to artifacts and modality differences, while allowing fully automated non-linear image warping at multiple scales via a hierarchical B-spline mesh grid. In addition, since routine clinical imaging procedures often involve the acquisition of multiple imaging protocols, we present a technique termed Multi-attribute Combined Mutual Information (MACAMI) to leverage the availability of multiple image sets to improve registration. We apply our registration techniques to a unique clinical dataset comprising 150 sets of in vivo MRI and post-operative WMH images from 25 patient studies in order to retrospectively establish the spatial extent of prostate cancer (CaP) on structural (T2-w) and functional (DCE) in vivo MRI. Accurate mapping of CaP on MRI is used to facilitate the development and evaluation of a system for computer-assisted detection (CAD) of CaP on multiprotocol MRI. We also demonstrate our registration and CAD algorithms in developing radiation therapy treatment plans that provide dose escalation to CaP by elastically registering diagnostic MRI with planning CT.

In November 1999, the Institute of Medicine, in consultation with the Commission on Life Sciences, the Commission on Physical Sciences, Mathematics, and Applications, and the Board on Science, Technology and Economic Policy launched a one year study on technologies for early detection of breast cancer. The committee was asked to examine technologies under development for early breast cancer detection, and to scrutinize the process of medical technology development, adoption, and dissemination. The committee is gathering information on these topics for its report in a number of ways, including two public workshops that bring in outside expertise. The first workshop on "Developing Technologies for Early Breast Cancer Detection" was held in Washington DC in February 2000. The content of the presentations at the workshop is summarized here. A second workshop, which will focus on the process of technology development and adoption, will be held in Washington, DC on June 19-20. A formal report on these topics, including conclusions and recommendations, will be prepared by the committee upon completion of the one-year study.

This book highlights the use of LEDs in biomedical photoacoustic imaging. In chapters written by key opinion leaders in the field, it covers a broad range of topics, including fundamentals, principles, instrumentation, image reconstruction and data/image processing methods, preclinical and clinical applications of LED-based photoacoustic imaging. Apart from preclinical imaging studies and early clinical pilot studies using LED-based photoacoustics, the book includes a chapter exploring the opportunities and challenges of clinical translation from an industry perspective. Given its scope, the book will appeal to scientists and engineers in academia and industry, as well as medical experts interested in the clinical applications of photoacoustic imaging.

Imaging in Dermatology covers a large number of topics in dermatological imaging, the use of lasers in dermatology studies, and the implications of using these technologies in research. Written by the experts working in these exciting fields, the book explicitly addresses not only current applications of nanotechnology, but also discusses future trends of these ever-growing and rapidly changing fields, providing clinicians and researchers with a clear understanding of the advantages and challenges of laser and imaging technologies in skin medicine today, along with the cellular and molecular effects of these technologies. - Outlines the fundamentals of imaging and lasers for dermatology in clinical and research settings - Provides knowledge of current and future applications of dermatological imaging and lasers - Coherently structured book written by the experts working in the fields covered

Second-harmonic generation (SHG) microscopy has shown great promise for imaging live cells and tissues, with applications in basic science, medical research, and tissue engineering. Second Harmonic Generation Imaging offers a complete guide to this optical modality, from basic principles, instrumentation, methods, and image analysis to biomedical a

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.