ISKOPAVANJA U ASERIJI

Zbog iznimne važnosti teksta za izučavanje Aserije, koji je tiskan 1908. godine, uredništvo časopisa se odlučilo na objavu prevoda. Izvornik: H. LIEBL, W. WILBERG, Ausgrabungen in Asseria, Jahreshefte des Österreichischen Archäologischen Instituts, 11, Wien, 1908., 17-88

Bone Mineral Density Estimations From Routine Multidetector Computed Tomography: A Comparative Study of Contrast and Calibration Effects.

INTRODUCTION Phantom-based (synchronous and asynchronous) and phantomless (internal tissue calibration based) assessment of bone mineral density (BMD) in routine MDCT (multidetector computed tomography) examinations potentially allows for diagnosis of osteoporosis. Although recent studies investigated the effects of contrast-medium application on phantom-calibrated BMD measurements, it remains uncertain to what extent internal tissue-calibrated BMD measurements are also susceptible to contrast-medium associated density variation. The present study is the first to systemically evaluate BMD variations related to contrast application comparing different calibration techniques. PURPOSE To compare predicative performance of different calibration techniques for BMD measurements obtained from triphasic contrast-enhanced MDCT. MATERIALS AND METHODS Bone mineral density was measured on nonenhanced (NE), arterial (AR) and portal-venous (PV) contrast phase MDCT images of 46 patients using synchronous (SYNC) and asynchronous (ASYNC) phantom calibration as well as internal calibration (IC). Quantitative computed tomography (QCT) served as criterion standard. Density variations were analyzed for each contrast phase and calibration technique, and respective linear fitting was performed. RESULTS Both asynchronous calibration-derived BMD values (NE-ASYNC) and values estimated using IC (NE-IC) on NE MDCT images did reasonably well in predicting QCT BMD (root-mean-square deviation, 8.0% and 7.8%, respectively). Average NE-IC BMD was 2.7% lower when compared with QCT (P = 0.017), whereas no difference could be found for NE-ASYNC (P = 0.957). All average BMD estimates derived from contrast-enhanced scans differed significantly from QCT BMD (all P 6.0 mg/mL). All regression fits revealed a consistent linear dependency (R range, 0.861-0.963). Overall accuracy and goodness of fit tended to decrease from AR to PV contrast phase. Highest precision and best linear fit could be reached using a synchronously scanned phantom (root-mean-square deviation, 9.4% for AR and 14.4% for PV). Both ASYNC and IC estimations performed comparably accurate and precise. CONCLUSIONS Our data suggest that internal calibration driven BMD measurements derived from contrast-enhanced MDCT need the same amount of post hoc contrast-effect adjustment as measurements using phantom calibration. Adjustment using linear correction equations can correct for systematic bias of bone density variations related to contrast application, irrespective of the calibration technique used

MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedbackComment: 16 page

Die Disticha Cornuti, auch Cornutus oder Distigium des Jo. v. Carlaudia genannt, und der Scholiast Cornutus : mit dem Text des Cornutus antiquus und novus

vom Kgl. Studienlehrer Hans Lieb

Beiträge zu den Persius-Scholien

vom Kgl. Studienlehrer Hans Lieb

ISKOPAVANJA U ASERIJI

Zbog iznimne važnosti teksta za izučavanje Aserije, koji je tiskan 1908. godine, uredništvo časopisa se odlučilo na objavu prevoda. Izvornik: H. LIEBL, W. WILBERG, Ausgrabungen in Asseria, Jahreshefte des Österreichischen Archäologischen Instituts, 11, Wien, 1908., 17-88