Dr. Lukasz Fura Profile

Dr. Lukasz Fura

at Institute of Fundamental Technological Research

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Publications (2)

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Proceedings Article | 29 March 2024 Poster + Paper

Analysis of uncertainty in accuracy of the reference segmentation of ultrasound images of breast tumors

Lukasz Fura, Anna Pawlowska, Anna Cwierz-Pienkowska, Agnieszka Domalik, Dominika Jagus, Piotr Kasprzak, Rafal Matkowski, Norbert Zolek

Proceedings Volume 12929, 1292911 (2024) https://doi.org/10.1117/12.3006442

KEYWORDS: Tumors, Image segmentation, Ultrasonography, Breast, Machine learning, Analytical research, Uncertainty analysis, Oncology, Reproducibility

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Manual image segmentations are naturally subject to inaccuracies related to systematic errors (due to the tools used, eye-hand coordination, etc.). This was noted earlier when a simplified accuracy scale was proposed [1]. This scale arbitrarily divides a given range of values of the Kappa measurement parameter into classes: almost perfect (>0.80), substantial (0.61 - 0.80), moderate (0.41 - 0.60), fair (0.21 - 0.40), slight (0.00 - 0.21) and poor (< 0.00). However, the determination of threshold values between classes is not entirely clear and seems to be application-dependent. This is particularly important for images in which the tumor-normal tissue boundary can be very indistinct, as is observed in ultrasound imaging of the most common cancer in women - breast cancer [2]. In machine learning, there is an ongoing contest over the values of performance indicators obtained from new neural network architecture without accounting for any ground truth bias. This raises the question of what relevance, from a segmentation quality point of view, a gain at the level of single percentages has [3] if the references have much greater uncertainty. So far, research on this topic has been limited. The relationship between the segmentations of breast tumors on ultrasound images provided by three radiologists and those obtained using deep learning model has been studied in [4]. Unfortunately, the indicated segmentation contour sometimes varied widely in all three cases. A cursory analysis by multiple physicians, which focused only on the Kappa coefficient in the context of physicians’ BI-RADS category assignments, was conducted in the [5]. In this article, we present a preliminary analysis of the accuracy of experts’ manually prepared binary breast cancer masks on ultrasound images and their impact on performance metrics commonly used in machine learning. In addition, we examined how tumor type or BI-RADS category [6] affects the accuracy of tumor contouring.

Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Numerical simulations and experimental verification of the extent of HIFU-induced tissue necrosis

Lukasz Fura, Norbert Zolek, Tamara Kujawska

Proceedings Volume 12034, 120342O (2022) https://doi.org/10.1117/12.2608140

KEYWORDS: Tissues, Numerical simulations, Acoustics, Magnetic resonance imaging, Wave propagation, Tumors, Computer simulations

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Local ultrasonic tissue ablation is induced by a rapid (<3s) rise in temperature in a small ellipsoidal volume (about 13mm3) inside the tissue to a cytotoxic level when exposed to a high-intensity focused ultrasound (HIFU) beam. The aim of this study was to develop a numerical tool to predict the location and extent of a necrotic lesion formed locally inside the ex vivo tissue as a result of exposure to a single or multiple HIFU beam, ensuring the efficacy and safety of destroying solid tumors. The proposed tool was based on modelling the non-linear propagation of acoustic waves and heat transfer in heterogeneous media using the k-wave toolbox. The wave propagation equations were solved for two-layer (water/tissue) media. The source of the acoustic waves was a spherical bowl-shaped transducer with a resonance frequency of 1.08 MHz. The distribution of heat sources was determined from the calculated acoustic pressure distribution in the HIFU beam. The obtained temperature distributions during heating and cooling allowed calculation of the thermal dose and prediction of the extent of the necrotic lesion. The obtained results of numerical simulations were compared with the experimental data from previous studies. The mean difference between the calculated and measured length or diameter of a single exposure induced necrotic lesion was approximately 1 mm. In the case of a necrotic lesion induced by multiple exposures, the mean difference between the measured and calculated cross-sectional area of the planned necrotic lesion covered with necrosis was approximately 11.2 %.

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