18 research outputs found
Robust GPU-based Virtual Reality Simulation of Radio Frequency Ablations for Various Needle Geometries and Locations
Purpose: Radio-frequency ablations play an important role in the therapy of
malignant liver lesions. The navigation of a needle to the lesion poses a
challenge for both the trainees and intervening physicians. Methods: This
publication presents a new GPU-based, accurate method for the simulation of
radio-frequency ablations for lesions at the needle tip in general and for an
existing visuo-haptic 4D VR simulator. The method is implemented real-time
capable with Nvidia CUDA. Results: It performs better than a literature method
concerning the theoretical characteristic of monotonic convergence of the
bioheat PDE and a in vitro gold standard with significant improvements (p <
0.05) in terms of Pearson correlations. It shows no failure modes or
theoretically inconsistent individual simulation results after the initial
phase of 10 seconds. On the Nvidia 1080 Ti GPU it achieves a very high frame
rendering performance of >480 Hz. Conclusion: Our method provides a more robust
and safer real-time ablation planning and intraoperative guidance technique,
especially avoiding the over-estimation of the ablated tissue death zone, which
is risky for the patient in terms of tumor recurrence. Future in vitro
measurements and optimization shall further improve the conservative estimate.Comment: 18 pages, 14 figures, 1 table, 2 algorithms, 2 movie
Quantitative and Qualitative Evaluation of Transforming to Flipped-Classroom from Instruction Teaching using Micro Feedback
Recently, the institutionalized transformation of frontal instruction classrooms into active learning spaces to foster the concept of (inter-)active learning has gained increasing attention. To investigate the impact of elements of active learning on learning reception of students in an advanced small sized MSc STEM course (<25 students), a traditional instructor teaching style class was transformed to flipped-classroom teaching. Before and after each lecture, anonymized evaluation Likert items from the students were recorded. Thus, both teaching styles for every given lecture were covered equally. In both classrooms, some didactic and methodological elements were kept constant, while others were changed when flipped-classroom took over semester midterm. Qualitative and quantitative results indicated that the flipped-classroom format generated greater learning effects as well as classroom enjoyment, fostered students’ self-regulated learning, enhanced group interaction, stimulated group activity and guaranteed a more synergistic learning behavior
3D Bounding Box Detection in Volumetric Medical Image Data: A Systematic Literature Review
This paper discusses current methods and trends for 3D bounding box detection
in volumetric medical image data. For this purpose, an overview of relevant
papers from recent years is given. 2D and 3D implementations are discussed and
compared. Multiple identified approaches for localizing anatomical structures
are presented. The results show that most research recently focuses on Deep
Learning methods, such as Convolutional Neural Networks vs. methods with manual
feature engineering, e.g. Random-Regression-Forests. An overview of bounding
box detection options is presented and helps researchers to select the most
promising approach for their target objects.Comment: 10 pages, 5 figures, 1 tabl
Comparison of 2D vs. 3D Unet Organ Segmentation in abdominal 3D CT images
A two-step concept for 3D segmentation on 5 abdominal organs inside volumetric CT images is presented. Firsteach relevant organ’s volume of interest is extracted as bounding box. The extracted volume acts as input for asecond stage, wherein two compared U-Nets with different architectural dimensions re-construct an organ segmen-tation as label mask. In this work, we focus on comparing 2D U-Nets vs. 3D U-Net counterparts. Our initial resultsindicate Dice improvements of about 6% at maximum. In this study to our surprise, liver and kidneys for instancewere tackled significantly better using the faster and GPU-memory saving 2D U-Nets. For other abdominal keyorgans, there were no significant differences, but we observe highly significant advantages for the 2D U-Net interms of GPU computational efforts for all organs under study