Bildverarbeitung F R Die Medizin 2008

In den letzten Jahren hat sich der Workshop „Bildverarbeitung für die Medizin" erfolgreich etabliert. Ziel ist es, aktuelle Forschungsergebnisse darzustellen und den Dialog zwischen Wissenschaftlern, Industrie und Anwendern zu vertiefen. Die Beiträge der Workshop-Dokumentation - einige in englischer Sprache - behandeln alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung, CAD, Segmentierung, Bildanalyse, Computerunterstützte Diagnose, Therapieplanung sowie deren klinische Anwendungen.

Auch 2009 hat der Workshop „Bildverarbeitung für die Medizin" erneut zum Ziel, aktuelle Forschungsergebnisse darzustellen und den Dialog zwischen Wissenschaftlern, Industrie und Anwendern zu vertiefen. Die Beiträge des Bandes - einige in englischer Sprache - behandeln alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung, CAD, Segmentierung, Bildanalyse, Visualisierung und Animation, Roboter und Manipulatoren, Chirurgische Simulatoren, Diagnose, Therapieplanung sowie deren klinische Anwendungen.

Heike Hufnagel develops a mathematically sound statistical shape model. Due to the particular attributes of the model, the challenging integration of explicit and implicit representations can be performed in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation method.

In den letzten Jahren hat sich der Workshop "Bildverarbeitung für die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2012 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespräche zwischen Wissenschaftlern, Industrie und Anwendern. Die Beiträge dieses Bandes - einige davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere Algorithmen, Hard- und Softwaresysteme sowie deren klinische Anwendung, u.a.: Bildgebung und -akquisition, Sichtbares Licht, Endoskopie, Mikroskopie, Visualisierung und Animation, Patientenindividuelle Simulation und Planung, Computerunterstützte Diagnose, Biomechanische Modellierung, Computergestützte Operationsplanung, Bildverarbeitung in der Telemedizin, Bildgestützte Roboter und Chirurgische Simulatoren.

The13thInternationalConferenceonMedicalImageComputingandComputer- Assisted Intervention, MICCAI 2010, was held in Beijing, China from 20-24 September,2010.ThevenuewastheChinaNationalConventionCenter(CNCC), China’slargestandnewestconferencecenterwith excellentfacilities andaprime location in the heart of the Olympic Green, adjacent to characteristic constr- tions like the Bird’s Nest (National Stadium) and the Water Cube (National Aquatics Center). MICCAI is the foremost international scienti?c event in the ?eld of medical image computing and computer-assisted interventions. The annual conference has a high scienti?c standard by virtue of the threshold for acceptance, and accordingly MICCAI has built up a track record of attracting leading scientists, engineersandcliniciansfromawiderangeoftechnicalandbiomedicaldisciplines. This year, we received 786 submissions, well in line with the previous two conferences in New York and London. Three program chairs and a program committee of 31 scientists, all with a recognized standing in the ?eld of the conference, were responsible for the selection of the papers. The review process was set up such that each paper was considered by the three program chairs, two program committee members, and a minimum of three external reviewers. The review process was double-blind, so the reviewers did not know the identity of the authors of the submission. After a careful evaluation procedure, in which all controversialand gray area papers were discussed individually, we arrived at a total of 251 accepted papers for MICCAI 2010, of which 45 were selected for podium presentation and 206 for poster presentation. The acceptance percentage (32%) was in keeping with that of previous MICCAI conferences. All 251 papers are included in the three MICCAI 2010 LNCS volumes.

This book provides a comprehensive introduction to current state-of-the-art auto-segmentation approaches used in radiation oncology for auto-delineation of organs-of-risk for thoracic radiation treatment planning. Containing the latest, cutting edge technologies and treatments, it explores deep-learning methods, multi-atlas-based methods, and model-based methods that are currently being developed for clinical radiation oncology applications. Each chapter focuses on a specific aspect of algorithm choices and discusses the impact of the different algorithm modules to the algorithm performance as well as the implementation issues for clinical use (including data curation challenges and auto-contour evaluations). This book is an ideal guide for radiation oncology centers looking to learn more about potential auto-segmentation tools for their clinic in addition to medical physicists commissioning auto-segmentation for clinical use. Features: Up-to-date with the latest technologies in the field Edited by leading authorities in the area, with chapter contributions from subject area specialists All approaches presented in this book are validated using a standard benchmark dataset established by the Thoracic Auto-segmentation Challenge held as an event of the 2017 Annual Meeting of American Association of Physicists in Medicine

The two-volume set LNCS 5761 and LNCS 5762 constitute the refereed proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, held in London, UK, in September 2009. Based on rigorous peer reviews, the program committee carefully selected 259 revised papers from 804 submissions for presentation in two volumes. The first volume includes 125 papers divided in topical sections on cardiovascular image guided intervention and robotics; surgical navigation and tissue interaction; intra-operative imaging and endoscopic navigation; motion modelling and image formation; image registration; modelling and segmentation; image segmentation and classification; segmentation and atlas based techniques; neuroimage analysis; surgical navigation and robotics; image registration; and neuroimage analysis: structure and function.

Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.