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Albiol, A., Corbi, A., & Albiol, F. (2017). Automatic intensity windowing of mammographic images based on a perceptual metric. Med. Phys., 44(4), 1369–1378.
Abstract: Purpose: Initial auto-adjustment of the window level WL and width WW applied to mammographic images. The proposed intensity windowing (IW) method is based on the maximization of the mutual information (MI) between a perceptual decomposition of the original 12-bit sources and their screen displayed 8-bit version. Besides zoom, color inversion and panning operations, IW is the most commonly performed task in daily screening and has a direct impact on diagnosis and the time involved in the process. Methods: The authors present a human visual system and perception-based algorithm named GRAIL (Gabor-relying adjustment of image levels). GRAIL initially measures a mammogram's quality based on the MI between the original instance and its Gabor-filtered derivations. From this point on, the algorithm performs an automatic intensity windowing process that outputs the WL/WW that best displays each mammogram for screening. GRAIL starts with the default, high contrast, wide dynamic range 12-bit data, and then maximizes the graphical information presented in ordinary 8-bit displays. Tests have been carried out with several mammogram databases. They comprise correlations and an ANOVA analysis with the manual IW levels established by a group of radiologists. A complete MATLAB implementation of GRAIL is available at . Results: Auto-leveled images show superior quality both perceptually and objectively compared to their full intensity range and compared to the application of other common methods like global contrast stretching (GCS). The correlations between the human determined intensity values and the ones estimated by our method surpass that of GCS. The ANOVA analysis with the upper intensity thresholds also reveals a similar outcome. GRAIL has also proven to specially perform better with images that contain micro-calcifications and/or foreign X-ray-opaque elements and with healthy BI-RADS A-type mammograms. It can also speed up the initial screening time by a mean of 4.5 s per image. Conclusions: A novel methodology is introduced that enables a quality-driven balancing of the WL/WW of mammographic images. This correction seeks the representation that maximizes the amount of graphical information contained in each image. The presented technique can contribute to the diagnosis and the overall efficiency of the breast screening session by suggesting, at the beginning, an optimal and customized windowing setting for each mammogram.
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Ma, Y. Z., Vijande, J., Ballester, F., Tedgren, A. C., Granero, D., Haworth, A., et al. (2017). A generic TG-186 shielded applicator for commissioning model-based dose calculation algorithms for high-dose-rate Ir-192 brachytherapy. Med. Phys., 44(11), 5961–5976.
Abstract: PurposeA joint working group was created by the American Association of Physicists in Medicine (AAPM), the European Society for Radiotherapy and Oncology (ESTRO), and the Australasian Brachytherapy Group (ABG) with the charge, among others, to develop a set of well-defined test case plans and perform calculations and comparisons with model-based dose calculation algorithms (MBDCAs). Its main goal is to facilitate a smooth transition from the AAPM Task Group No. 43 (TG-43) dose calculation formalism, widely being used in clinical practice for brachytherapy, to the one proposed by Task Group No. 186 (TG-186) for MBDCAs. To do so, in this work a hypothetical, generic high-dose rate (HDR) Ir-192 shielded applicator has been designed and benchmarked. MethodsA generic HDR Ir-192 shielded applicator was designed based on three commercially available gynecological applicators as well as a virtual cubic water phantom that can be imported into any DICOM-RT compatible treatment planning system (TPS). The absorbed dose distribution around the applicator with the TG-186 Ir-192 source located at one dwell position at its center was computed using two commercial TPSs incorporating MBDCAs (Oncentra((R)) Brachy with Advanced Collapsed-cone Engine, ACE, and BrachyVision ACUROS) and state-of-the-art Monte Carlo (MC) codes, including ALGEBRA, BrachyDose, egs_brachy, Geant4, MCNP6, and Penelope2008. TPS-based volumetric dose distributions for the previously reported source centered in water and source displaced test cases, and the new source centered in applicator test case, were analyzed here using the MCNP6 dose distribution as a reference. Volumetric dose comparisons of TPS results against results for the other MC codes were also performed. Distributions of local and global dose difference ratios are reported. ResultsThe local dose differences among MC codes are comparable to the statistical uncertainties of the reference datasets for the source centered in water and source displaced test cases and for the clinically relevant part of the unshielded volume in the source centered in applicator case. Larger local differences appear in the shielded volume or at large distances. Considering clinically relevant regions, global dose differences are smaller than the local ones. The most disadvantageous case for the MBDCAs is the one including the shielded applicator. In this case, ACUROS agrees with MC within [-4.2%, +4.2%] for the majority of voxels (95%) while presenting dose differences within [-0.12%, +0.12%] of the dose at a clinically relevant reference point. For ACE, 95% of the total volume presents differences with respect to MC in the range [-1.7%, +0.4%] of the dose at the reference point. ConclusionsThe combination of the generic source and generic shielded applicator, together with the previously developed test cases and reference datasets (available in the Brachytherapy Source Registry), lay a solid foundation in supporting uniform commissioning procedures and direct comparisons among treatment planning systems for HDR Ir-192 brachytherapy.
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Hirn, J., Garcia, J. E., Montesinos-Navarro, A., Sanchez-Martin, R., Sanz, V., & Verdu, M. (2022). A deep Generative Artificial Intelligence system to predict species coexistence patterns. Methods Ecol. Evol., 13, 1052–1061.
Abstract: Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge.
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Valdes-Cortez, C., Niatsetski, Y., Perez-Calatayud, J., Ballester, F., & Vijande, J. (2022). A Monte Carlo study of the relative biological effectiveness in surface brachytherapy. Med. Phys., 49, 5576–5588.
Abstract: Purpose This work aims to simulate clustered DNA damage from ionizing radiation and estimate the relative biological effectiveness (RBE) for radionuclide (rBT)- and electronic (eBT)-based surface brachytherapy through a hybrid Monte Carlo (MC) approach, using realistic models of the sources and applicators. Methods Damage from ionizing radiation has been studied using the Monte Carlo Damage Simulation algorithm using as input the primary electron fluence simulated using a state-of-the-art MC code, PENELOPE-2018. Two Ir-192 rBT applicators, Valencia and Leipzig, one Co-60 source with a Freiburg Flap applicator (reference source), and two eBT systems, Esteya and INTRABEAM, have been included in this study implementing full realizations of their geometries as disclosed by the manufacturer. The role played by filtration and tube kilovoltage has also been addressed. Results For rBT, an RBE value of about 1.01 has been found for the applicators and phantoms considered. In the case of eBT, RBE values for the Esteya system show an almost constant RBE value of about 1.06 for all depths and materials. For INTRABEAM, variations in the range of 1.12-1.06 are reported depending on phantom composition and depth. Modifications in the Esteya system, filtration, and tube kilovoltage give rise to variations in the same range. Conclusions Current clinical practice does not incorporate biological effects in surface brachytherapy. Therefore, the same absorbed dose is administered to the patients independently on the particularities of the rBT or eBT system considered. The almost constant RBE values reported for rBT support that assumption regardless of the details of the patient geometry, the presence of a flattening filter in the applicator design, or even significant modifications in the photon energy spectra above 300 keV. That is not the case for eBT, where a clear dependence on the eBT system and the characteristics of the patient geometry are reported. A complete study specific for each eBT system, including detailed applicator characteristics (size, shape, filtering, among others) and common anatomical locations, should be performed before adopting an existing RBE value.
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SCiMMA and SNEWS Collaborations(Baxter, A. L. et al), & Colomer, M. (2022). Collaborative experience between scientific software projects using Agile Scrum development. Softw.-Pract. Exp., 52, 2077–2096.
Abstract: Developing sustainable software for the scientific community requires expertise in software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for software engineering practices in the scientific community, and the complexity of developing for evolving scientific contexts. While open-source software can partially address these concerns, it can introduce complicating dependencies and delay development. These issues can be reduced if scientists and software developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi-Messenger Astrophysics project. The collaboration addressed the difficulties of open-source software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting a user-group while maintaining core development. These issues were mitigated by creating a second Agile Scrum framework in parallel with the developers' ongoing Agile Scrum process. This Agile collaboration promoted communication, ensured that the scientists had an active role in development, and allowed the developers to evaluate and implement the scientists' software requirements. The collaboration provided benefits for each group: the scientists actuated their development by using an existing platform, and the developers utilized the scientists' use-case to improve their systems. This case study suggests that scientists and software developers can avoid scientific computing issues by collaborating and that Agile Scrum methods can address emergent concerns.
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