International Journal of Computer Assisted Radiology and Surgery This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans
ConclusionsUsing a CNN model, the proposed method for lung parenchyma segmentation produced precise segmentation results. Furthermore, the post-processing algorithm addressed false positives and negatives in the model ’s predictions. Overall, the proposed approach demonstrated promising results for lung parenchyma segmentation. The method has the potential to be valuable in the advancement of computer-aided diagnosis (CAD) systems for automatic nodule detection. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 18, 2023 Category: Intensive Care Source Type: research

Quantitative validation of two model-based methods for the correction of probe pressure deformation in ultrasound
ConclusionThe proposed methods ensured the correction of the deformed images induced by a linear probe pressure without using any information coming from sensors (force or position), or generic information about the mechanical parameters. The corrected images can be used to obtain a corrected 3D US image. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 18, 2023 Category: Intensive Care Source Type: research

Comparative evaluation of uncertainty estimation and decomposition methods on liver segmentation
ConclusionsMutual information decomposition is simple to implement, has mathematically pleasing properties, and yields meaningful uncertainty estimates that behave as expected under controlled changes to our data set. The additional extension of BNNs with loss-attenuating neurons provides no improvement in terms of segmentation performance or calibration in our setting, but marginal benefits regarding the quality of decomposed uncertainties. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 16, 2023 Category: Intensive Care Source Type: research

Toward a navigation framework for fetoscopy
ConclusionThis work introduces a learning-based framework for placental mosaicking with occlusion recovery from intra-operative videos using a keypoint-based strategy and features. The proposed framework can compute the placental panorama and recover even in case of camera tracking loss where other methods fail. The results suggest that the proposed framework has large potential to pave the way to creating a surgical navigation system for TTTS by providing robust field-of-view expansion. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 16, 2023 Category: Intensive Care Source Type: research

Novel and inexpensive gamma radiation sensor: initial concept and design
ConclusionsAfter successful first experiments with a single diode, the optimal spatial arrangement of the diodes as well as their orientation will be determined to achieve a compact, cost effective yet fast, and accurate sensor device for every-day clinical application. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 11, 2023 Category: Intensive Care Source Type: research

A cGAN-based network for depth estimation from bronchoscopic images
ConclusionsIncluding virtual and real bronchoscopic images in the training phase of the depth estimation networks can improve depth estimation ’s performance on both synthetic and real scenes. Further validation of this work is planned on 3D clinical phantoms. Based on the depth estimation results obtained in this work, the accuracy of locating bronchoscopes with corresponding pre-operative CTs will also be evaluated in comparison with t he current clinical status. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 10, 2023 Category: Intensive Care Source Type: research

Correction to: Nail it! vision-based drift correction for accurate mixed reality surgical guidance
(Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 5, 2023 Category: Intensive Care Source Type: research

Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-up
ConclusionThe classification of lesion classification provides the clinician with a readily accessible and intuitive identification and classification of the lesion changes and their patterns in support of clinical decision making. Comprehensive automatic computer-aided lesion matching and analysis of lesion changes may improve quantitative follow-up and evaluation of disease status, assessment of treatment efficacy and response to therapy. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - August 4, 2023 Category: Intensive Care Source Type: research