A novel framework for differentiating vessel-like objects in coronarography images.

Coronary Artery Disease is the leading cause of death worldwide. Its prevalence will grow while access to specialized medical care will be further limited due to staff shortages. Therefore, any facilitation of diagnosis or treatment is of paramount importance. The diagnosis based on Coronary Angiography can be automated to perform a quantitative evaluation of lesions. This requires precise segmentation of coronary arteries. At the moment, the state-of-the-art algorithms fail to eliminate vessel-like artifacts that are wrongly included in segmentation results (e.g. catheters, stitches). This is a bottleneck for the automatization of the diagnosis workflow that precedes clinical action. In this paper, we propose a 2-step post-segmentation refinement algorithm. A binary segmentation of the coronary arteries is used to extract image features - inputs for an XGBoost Classifier. Its predictions are improved by a neighborhood filter that leverages contextual information to assign correct labels. The algorithm is primarily concerned with differentiating vessels from other vessel-like objects and does so with a 99% accuracy rate. It takes advantage of an original local description of Tamura features, which proved to be one of the most influential factors in decision-making. As a result, the segmentation of coronary arteries is cleaned from artifacts, enabling AI-supported diagnosis workflows to be automated. After re-training, the proposed method can be used to eliminate post-segmentation artifacts in other medical domains.Clinical relevance- The algorithm proposed in this paper allows for the development of software that could automatically calculate the Syntax Score in real time. This would shorten diagnostics time and allow for immediate action in critical cases.

Novel and inexpensive gamma radiation sensor: initial concept and design.

PURPOSE: Early detection of tumors and their spread, particularly in lymph node illnesses, is critical for a full recovery. However, it is currently difficult due to a lack of imaging or detection devices that provide the necessary spatial depth and location information. Consequently, it would be beneficial to have a simple and cost-effective sensor device to determine the 3D position of, e.g., a lymph node in the patient's coordinate system. METHODS: In this work, we present a concept and design for a novel semiconductor-based 3D detection system that uses inexpensive off-the-shelf components to measure gamma activity. A simple Arduino-type microcontroller calculates the 3D position of the probe based on the number of the measured pulse, the spatial sensitivity characteristics, and the known geometry of the device. RESULTS: The system was set up from four photodiodes (Osram BPW34), a transistor-based pre-amplifier, and a two-stage operational amplifier as the main stage. Doing so, a signal sufficient to be read by the microcontroller could be produced. The performed calculations proved that for a system consisting of at least four photodiodes, it is possible to determine precise location of a gamma radiation source. CONCLUSIONS: After 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.

Study of needle punctures into soft tissue through audio and force sensing: can audio be a simple alternative for needle guidance?

PURPOSE: Percutaneous needle insertion is one of the most common minimally invasive procedures. The clinician's experience and medical imaging support are essential to the procedure's safety. However, imaging comes with inaccuracies due to artifacts, and therefore sensor-based solutions were proposed to improve accuracy. However, sensors are usually embedded in the needle tip, leading to design limitations. A novel concept was proposed for capturing tip-tissue interaction information through audio sensing, showing promising results for needle guidance. This work demonstrates that this audio approach can provide important puncture information by comparing audio and force signal dynamics during insertion. METHODS: An experimental setup for inserting a needle into soft tissue was prepared. Audio and force signals were synchronously recorded at four different insertion velocities, and a dataset of 200 recordings was acquired. Indicators related to different aspects of the force and audio were compared through signal-to-signal and event-to-event correlation analysis. RESULTS: High signal-to-signal correlations between force and audio indicators regardless of the insertion velocity were obtained. The force curvature indicator obtained the best correlation performances to audio with more than [Formula: see text] of the correlations higher than 0.6. The event-to-event correlation analysis shows that a puncture event in the force is generally identifiable in audio and that their intensities firmly related. CONCLUSIONS: Audio contains valuable information for monitoring needle tip/tissue interaction. Significant dynamics obtained from a well-known sensor as force can also be extracted from audio, regardless of insertion velocities.

A 3D model of the renal vasculature - a joined result of the corrosion casting technique, micro-CT imaging and rapid prototyping technology.

Three-dimensional (3D) printed model of the renal vasculature shows a high level of accuracy of subsequent divisions of both the arterial and the venous tree. However, minor artifacts appeared in the form of oval endings to the terminal branches of the vascular tree, contrary to the anticipated sharply pointed segments. Unfortunately, selective laser sintering process does not currently permit to present the arterial, venous and urinary systems in distinct colors, hence topographic relationship between the vascular and the pelvicalyceal systems is difficult to attain. Nonetheless, the 3D printed model can be used for educational purposes to demonstrate the vast renal vasculature and may also serve as a reference model whilst evaluating morphological anomalies of the intrarenal vasculature in a surgical setting.