Kristina Bliznakova, PhD
Technical University of Varna, Varna, Bulgaria
Dr. Eng. Kristina Bliznakova graduated in Electrical Engineering and Microelectronics at the Technical University of Varna in 1996. From 1996 to 1998 she was in the Master Program in Biomedical Engineering at the University of Patras, Greece. In 1998, he received a Master’s degree in Biomedical Engineering and in the same year he continued his doctoral dissertation in the same field. In 2003, he successfully defended a dissertation in the field of imaging diagnostics. Her dissertation ends with a method for creating anthropomorphic female models of female breasts designed for X-ray techniques. There are 40 publications in Impact-Actual Magazines. Member of the Bulgarian Society of Biomedical Physics and Engineering (BDBFI). Since August 2015 he has been chair of IEEE ED / SSC Chapter Varna.
Talk title: Three-dimensional breast cancer models for X-ray Imaging research
Breast cancer is by far the most frequently diagnosed cancer and the leading cause of cancer-related death among women worldwide. Despite technological advances, such as the digital mammography, the national screening programs, the introduction of the computer-aided design systems in clinical routine, screening and diagnosing of cancers hidden in breast dense parenchyma still remains a challenging task. New methods for early detection and correct diagnosis of breasts are needed. Dedicated machine learning systems may also assist in the detection and classification of the various types of the breast cancers. For this purpose, a large number of images containing different types of benign and malignant formations is required for their development and adjustment. The best approach, in this case, is to obtain simulated images of breast cancer. Thus, a realistic three-dimensional (3D) computational models of the breast tumors are a requirement.
Tumor modeling is an important part of the realistic breast modeling. Tumor models are built to be incorporated into the existing or developed breast models to further allow performing of reliable virtual studies in the field of breast imaging and cancer detectability and diagnosis.
In general, tumor modeling can be performed through two basic approaches: by segmentation of breast lesions from 3D patient images and by using mathematical modeling. The first approach is applied to patient images obtained from breast tomosynthesis and Computed Tomography (CT) modalities, as well as, cadaver samples scanned at CT. The whole procedure usually includes filtering of the original images in order to reduce the noise, binarization of the area of the lesion, applying morphological operations to remove the remaining artifacts and region growing techniques to segment the lesion. This procedure may be also applied to high-resolution 3D microCT images of breast histology samples, followed by image segmentation and further characterizing: sizes, shapes, type of abnormality.
The second approach is the mathematical modeling, which offers the undoubted advantage to parametrically describe the 3D shapes or their generation. The use of mathematical modeling strongly relies on 3D random walks, followed by a set of image processing operations, which aim to deliver a solid based tumor. The level of simulated details is related to the required model complexity and heavily depends on the available computational power.
Researchers from the biomedical engineering unit at the Technical University of Varna has started the development of a database (MaXIMA Project Database) with computational models of breast tumors with irregular and speculated shapes. The availability of such models is a powerful instrument in the hands of engineers, physicians, and physicists to be used in the development of new technologies for a precise definition of the boundaries of these cancers. This keynote speech will address the methods used in the generation of models of the breast cancer and their use in emerging x-ray breast imaging. Selected examples are presented from the current work of the biomedical engineering unit at Technical University of Varna, Bulgaria.
Sabareesh K P Velu, PhD
University of Information Science and Technology “St. Paul the Apostle” – Ohrid, Macedonia
Talk title: Micromanipulations of passive and active crowds with speckle optical tweezers
Optical tweezers have been used widely in physics, chemistry, and biology to manipulate and trap microscopic and nanoscopic objects, such as dielectric and metallic particles, living cells, organelles and macromolecules [1-3]. However, generating well-controlled optical forces usually requires a highly-focused laser beam, which means a careful engineering of the setup and the samples . Although similar conditions are routinely met in research laboratories, optical imperfections and scattering, limits the applicability of this technique to real-life situations, for example in biomedical and microfluidic applications. Nonetheless, scattering of coherent light by disordered structures gives rise to speckles [5-6], random diffraction patterns with well-defined statistical properties.
In this keynote speech, I will first introduce speckle optical tweezers (SOT) a simple, low-degree of control setup to manipulate microscopic passive particles to different diffusion regimes i.e., sub-diffusion, super-diffusion, and free diffusion using the statistical properties of speckle light fields.
In the second part of this speech, I will present some recent experimental results where a colloidal active matter system switches between gathering and dispersal of individuals in response to speckle light fields (noisy or disordered potential). Interestingly, the statistical properties of the noisy potential allow us to dynamically control the long-term collective behavior of the active matter system .
Beyond the fundamental interests, the results are significant to engineer autonomous agents interacting with realistic (complex and crowded) surroundings, as artificial microswimmers capable of localizing, picking up and delivering nanoscopic cargos, in catalysis, in bioremediation, chemical sensing and drug delivery.
- Sidhartha S. Jena, Hiren M. Joshi, K. P. V. Sabareesh, B. V. R. Tata and T. S. Rao. “Dynamics of deinococcus radiodurans under controlled growth conditions”. Biophysical Journal 91, 2699-2707 (2006).
- Sabareesh K. P. Velu, Minhao Yan, Kuo-Pi Tsung, Ken-Tsung Wong, Dario Bassani and Pierre Terech.“Spontaneous formation of artificial vesicles in organic media through hydrogen-bonding interactions”. Macromolecules 46, 1591-1598 (2013).
- Athanasia Kostopoulou, Sabareesh K. P. Velu, Kalaivani Thangavel, Francesco Orsini, Konstantinos Brintakis, Stylianos Psycharakis, Anthi Ranella, Lorenzo Bordonali, Alexandros Lappas and Alessandro Lascialfari. “Colloidal assemblies of oriented maghemite nanocrystals and their NMR relaxometric properties”. Dalton Transactions 43, 8395-8404 (2014).
- Ashkin. “Acceleration and trapping by particles by radiation pressure”. Physical Review Letters 24, 156 (1970).
- A. C. Potenza, K. P. V. Sabareesh, M. Carpineti, M. D. Alaimo and M. Giglio. “How to measure the optical thickness of scattering particles from the phase delay of scattered waves. Application to turbid samples”. Physical Review Letters 105, 193901 (2010).
- P. V. Sabareesh. “Near field speckles the optical theorem revisited”. arXiv:1801.04135v1 (2018).
- Ercağ Pince, Sabareesh K. P. Velu, Agnese Callegari, Parviz Elahi, Sylvain Gigan, Giovanni Volpe and Giorgio Volpe. “Disorder-mediated crowd control in an active matter system”. Nature Communications 7, 10907 (2016).