There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.

elastix : A Toolbox for Intensity-Based Medical Image Registration

Biomedical imaging is a driver of scientific discovery and a core component of medical care and is being stimulated by the field of deep learning. While semantic segmentation algorithms enable image analysis and quantification in many applications, the design of respective specialized solutions is non-trivial and highly dependent on dataset properties and hardware conditions. We developed nnU-Net, a deep learning-based segmentation method that automatically configures itself, including preprocessing, network architecture, training and post-processing for any new task. The key design choices in this process are modeled as a set of fixed parameters, interdependent rules and empirical decisions. Without manual intervention, nnU-Net surpasses most existing approaches, including highly specialized solutions on 23 public datasets used in international biomedical segmentation competitions. We make nnU-Net publicly available as an out-of-the-box tool, rendering state-of-the-art segmentation accessible to a broad audience by requiring neither expert knowledge nor computing resources beyond standard network training.

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Ductal carcinoma in situ (DCIS) of the breast represents a heterogeneous group of neoplastic lesions in the breast ducts. The goal for management of DCIS is to prevent the development of invasive breast cancer. This manuscript focuses on the NCCN Guidelines Panel recommendations for the workup, primary treatment, risk reduction strategies, and surveillance specific to DCIS.

https://www.unitypoint.org/desmoines/filesimages/Cancer%20Education/Oncology%20Nursing%20Conference/2015/2014%20NCCN%20Clin%20Pract%20Guidelines%20Male%20Sex%20Dysf.pdf

Clinical practice guidelines in oncology

Mass spectrometry imaging (MSI) is a label-free analysis method for resolving biomolecules or pharmaceuticals in the spatial domain. It offers unique perspectives for the examination of entire organs or other tissue specimens. Owing to increasing capabilities of modern MSI devices, the use of 3D and multi-modal MSI becomes feasible in routine applications — resulting in hundreds of gigabytes of data. 

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Abstract: M2aia: Mass Spectrometry Imaging Applications for Interactive Analysis in MITK

NAD+ loading of mammalian cells by electrotransfection leads to increased poly(ADP-ribosyl)ation capacity

In diesem Beitrag stellen wir einen neuartigen Atembewegungssimulator vor, welcher Experimente in bewegten Schweine- und Menschenlebern ermoglicht. Der Simulator ist mit relativ geringem Aufwand nachbaubar und eignet sich insbesondere zur in-vitro Evaluation von Weichgewebe-Navigationssystemen. Er besteht im Wesentlichen aus einem vereinfachten Modell des Korpus, welches die Befestigung einer Menschen- oder Schweineleber an ein kunstliches Zwerchfell (Plexiglasscheibe) vorsieht. Das Anschliesen einer Beatmungsmaschine an das Modell bewirkt eine periodische Bewegung der Leber. Durch Platzierung optisch trackbarer Nadeln in drei verschiedenen Schweinelebern zeigen wir, dass die durch den Simulator erzeugte Bewegung dieser Lebern im Korpusmodell mit der Bewegung einer Menschenleber im Korper qualitativ ubereinstimmt: (1) Die Leber wird entlang aller drei Achsen bewegt, jedoch hauptsachlich axial und (2) die Leber wird nicht nur rigide verschoben, sondern echt deformiert.

/pdf/atembewegungssimulator-fur-die-in-vitro-evaluation-von-1ptfj1zy1o.pdf

Atembewegungssimulator für die in-vitro Evaluation von Weichgewebe-Navigationssystemen in der Leber

During mitral valve reconstruction, intraoperative valve analysis is carried out by the cardiac surgeon for assessing location and extent of leaflet defects. The analysis of each leaflet segment is usually examined using two nerve hooks, as proposed by Carpentier. Qualitative comparison between the possible displacement of the segments is done in order to evaluate motion restriction or prolapse. However, this comparison depends on the subjective assessment and the experience of the surgeon. We propose a new computer-based approach which allows for a quantitative measurement of the segment displacement in relation to the annulus plane. Infrared reflecting markers are attached to the instruments for optical tracking. The segments are examined as proposed in the Carpentier method using either a single or two nerve hooks. Evaluation was carried out by repeating measurements three times on an excised porcine heart. Mean chordae were cut to induce a prolapse iatrogenically. The single-hook procedure turned out to be less time-consuming and easier to perform and showed a high reproducibility (mean standard deviation: 1.51 mm) in comparison to the hook-pair approach (3.35mm). Our method overcomes the limitations of actual subjective analysis, enables to get quantitative and highly reproducible measurements of leaflet prolapse and may provide valuable decision support during surgery.

http://www.cinc.org/archives/2014/pdf/0961.pdf

A new method for intraoperative quantification of mitral leaflet segment prolapse

Dreidimensionale Doppler-echokardiographische Verfahren liefern eine Vielzahl hochwertiger qualitativer und quantitativer diagnostischer Informationen, die fur die Operationsplanung und die funktionelle Auswertung der Operationsergebnisse von groser Bedeutung sind. Ein fur diesen Zweck neuentwickeltes Auswertesystem wird kurz vorgestellt. Auserdem werden Ergebnisse von in vivo und in vitro Studien zur Untersuchung verschiedener Methoden der Regurgitationsvolumetrie prasentiert.

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Ivo Wolf

Papers

Abstract: M2aia: Mass Spectrometry Imaging Applications for Interactive Analysis in MITK

NAD+ loading of mammalian cells by electrotransfection leads to increased poly(ADP-ribosyl)ation capacity

Atembewegungssimulator für die in-vitro Evaluation von Weichgewebe-Navigationssystemen in der Leber

A new method for intraoperative quantification of mitral leaflet segment prolapse

Neue dreidimensionale diagnostische Verfahren in der Herzchirurgie