Predavanja

Ponedeljkov fizikalni kolokvij

V ponedeljek, 19.11.2018, bo imel Urban Simončič predavanje v sklopu ponedeljkovih fizikalnih kolokvijev z naslovom Tracer kinetic modelling for medical image analysis. Predavanje bo ob 16:15 na Fakulteti za matematiko in fiziko, Jadranska 19, v predavalnici F1. Pred predavanjem so vsi poslušalci vljudno vabljeni na čaj.

Urban Simončič

Povzetek v angleščini:
Medical imaging measures biological or physical tissue properties. Tracer administration and dynamic image acquisition allows image analysis with tracer kinetic modelling. Application of that technique greatly increases the amount of information that is obtained with the imaging.
In the first part of this seminar I will present basic principle of medical imaging with the tracer, physiological pathways of tracers and models used for tracer kinetic modelling. In the second part I will focus on exemplary applications of tracer kinetic modelling for medical image analysis, relevant implementation details and interesting results.

Vloga medicinske fizike v času natančne medicine; prof. dr. Robert Jeraj

Vabimo vas na 18. predavanje iz sklopa “Kolokviji na IJS” v letu 2017/18, ki bo v sredo, 27. junija 2018, ob 13. uri v Veliki predavalnici Instituta »Jožef Stefan«  na Jamovi cesti 39 v Ljubljani. Napovednik predavanja najdete tudi na naslovu http://www.ijs.si/ijsw/Koledar_prireditev, posnetke preteklih predavanj pa na http://videolectures.net/kolokviji_ijs.

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prof. dr. Robert Jeraj

University of Wisconsin, Madison, ZDA
Univerza v Ljubljani, Ljubljana

 

Vloga medicinske fizike v času natančne medicine

Medicinska fizika je tesno povezana z medicino; zato se tudi razvija v podobni smeri. Ključni trend v medicini, predvsem onkologiji, je usmerjen v personalizacijo zdravljenja. Natančnejše profiliranje bolezenskega stanja je pripeljalo do t.i. »natančne medicine«.  Seveda pa ob tem prehodu ne gre brez težav. Tumorji, na primer, zaradi evolucije in evolucijskega odziva na zdravljenje postanejo s časom vedno težje ozdravljivi. Pri tem je ključnega pomena razumevanje rezistence na zdravljenje,  ki je povezana z močno heterogenostjo bolezni. Uporaba medicinskega slikanja, predvsem molekularnega slikanja, je ena od rešitev, ki jih ponuja medicinska fizika. V predavanju bomo predstavili nekaj primerov kliničnih študij na osnovi molekularnega slikanja, ki nam omogočajo unikaten vpogled v tumorsko heterogeneost, ter kompleksnost odziva tumorjev na zdravljenje. Predstavili bomo nekatere možnosti izboljšanja zdravljenja na podlagi teh novih ugotovitev. Hkrati pa bomo opozorili na izredno pomembno vlogo, ki jo igra (medicinska) fizika pri razvoju teh novih zdravljenj.

Predavanje bo v angleščini.

Lepo vabljeni!

Predavanje ob izvolitvi v naziv “znanstveni sodelavec”

V ponedeljek, 5. marca 2018, bo imel Urban Simončič predavanje v okviru izvolitve v naziv znanstveni sodelavec z naslovom Kvantifikacija PET slik s kinetično analizo – teorija in aplikacije. Predavanje bo ob 11:00 v zgornji sejni sobi Reaktorskega centra Podgorica. Vabljeni!
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Povzetek:
Pozitronska emisijska tomografija (PET) je tehnika molekularnega slikanja, ki ima pomembno vlogo v moderni medicini; predvsem v onkologiji, nevrologiji in kardiologiji. Kvantitativne metrike se iz slik PET lahko izpeljejo z normalizacijami privzema ali s kinetično analizo. Prednost kvantifikacije s kinetično analizo, v primerjavi z normalizacijo privzema je v obširnejših in bolj specifičnih rezultatih. V tem seminarju bo predstavljena tehnika slikanja PET, teoretične osnove za kinetično analizo, praktična implementacija in nekaj aplikacij v onkologiji.

Ponedeljkov fizikalni kolokvij

V ponedeljek, 8.1.2018, bo imel Matija Milanič predavanje v okviru izvolitve v naziv docenta z naslovom Hyperspectral imaging and medicine. Predavanje bo ob 16:15 na Fakulteti za matematiko in fiziko, Jadranska 19, predavalnica F1. Pred predavanjem so vsi poslušalci vljudno vabljeni na čaj.

Matija Milanič

Povzetek v angleščini:
Hyperspectral imaging (HSI) is a non-contact and non-invasive optical technique which provides both spectral and spatial information in one measurement. The goal of HSI is to find objects, identify materials, or detect processes. As such it became a promising imaging modality for medical applications, especially in disease diagnosis and image-guided surgery.
An overview of the technique will be given, including a review of possible medical applications with focus on evaluation of bruises and detection of small-joint arthritis.

Predavanje Ivana Štajduharja

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V sredo, 10.5.2017, ob 16ih vljudno vabimo na predavanje izr. prof. Ivana Štajduharja (Department of Computer Engineering, University of Rijeka – Faculty of Engineering) z naslovom Artificial Intelligence in Medicine. Predavanje bo potekalo v predavalnici F2 v prvem nadstropju stavbe za fiziko, Jadranska 19, Ljubljana.

Artificial Intelligence in Medicine

Would it be possible to supersede physicians with computers, to some extent, at least? The idea of computer-aided diagnosis in diagnosing and treating illnesses has been around from nineteen-eighties. It was then that scientists discovered that, by applying statistical algorithms on real-world patient data, using so-called machine learning, one can establish useful (almost-)out-of-the-box mathematical models that perform well at describing some problems. In the last decade, significant increases occurred worldwide in the level of informatics-readiness of clinical centres, in the availability of standardised technology for data exchange and storage, and in the abundance of quality medical radiology techniques. This, in turn, resulted in an explosion in the availability of voluminous data, enabling further advances in the field of computer-aided diagnosis and treatment. In this lecture, in addition to some fundamentals related to the field, several topics concerning medical image analysis will be discussed: learning predictive models for diagnosing knee injury, data preprocessing for reducing model complexity and transfer learning in medical radiology domain (“RadiologyNet”, a research project conducted in collaboration with the Clinical Hospital Centre Rijeka, Croatia).

Dan ščitnice in dobrodelna akcija “Pomagajmo ščitničnim bolnikom”

ThroidCancerV mesecu maju (26.5.) bo v prostorih Univerzitetnega kliničnega centra organizirano srečanje z naslovom “Dan ščitnice”. Ta dan bodo v predavalnici 1 UKCL potekala predavanja o hipertirozi, raku ščitnice in drugih boleznih. Preliminarni program si lahko ogledate na sledeči povezavi.

Že ta mesec pa poteka tudi dobrodelna akcija “Pomagajmo ščitničnim bolnikom” s katero se zbira sredstva za nakup sodobne ultrazvočne naprave za Ambulanto za bolezni ščitnice Klinike za nuklearno medicino UKC Ljubljana. Jutri (5.4.) bosta radio in TV Veseljak program namenila ščitničnim bolnikom v sodelovanju z znanimi gosti, predstavniki bolnikov in zdravniki specialisti za bolezni ščitnice. Na povezavi si lahko preberete več o dogodku ter kako lahko tudi vi prispevate k nakupu naprave.

Predavanje prof. Roberta Jeraja

V petek, 31.3.2017, bo imel profesor Robert Jeraj predavanje v sklopu ponedeljkovega fizikalnega kolokvija (tokrat izjemoma v petkovi izvedbi) z naslovom Implications of Tumor Heterogeneity for Precision Medicine. Predavanje bo ob 12:15 na Fakulteti za matematiko in fiziko, Jadranska 19, predavalnica F1. Pred predavanjem so vsi udeleženci vabljeni na čaj. Se vidimo!

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Medical physics is intimately connected with medicine, and is progressing along a similar path. General trend of medicine, particularly oncology, towards personalized treatment gave rise to precision medicine, which addresses the highly complex nature of disease. However, there are severe obstacles to overcome. For example, cancers evolve in time to become harder targets to treat. Understanding treatment resistance, and its development, often connected with the highly heterogeneous nature of the disease, is another key obstacle. Use of multi-modality imaging techniques such as molecular imaging is one of the solutions that medical physics can offer. Examples from clinical trials utilizing advanced molecular imaging, highlighting intra-tumor and inter-tumor heterogeneity will be presented. New understanding of cancer treatment response dynamics will be outlined. Potential for improved patient treatment designs steaming from these novel insights will be discussed.

Poljudni predavanji iz matematike in medicinske fizike

Fakulteta za matematiko in fiziko vabi na poljudni predavanji iz matematike in fizike!

Matematično predavanje bo že tretje iz cikla poljudnih matematičnih predavanj “I <3 MAT". Na njem se bo prof. dr. Boris Lavrič posvetil lepoti in eksaktnosti geometrije. Na fizikalnem predavanju pa nas bo prof. dr. Robert Jeraj prepričal zakaj je Fizika + Medicina = Medicinska fizika. Predavanji bosta v četrtek 30. 3. 2017, ob 18.00 in 19.00 na Jadranski 21 v predavalnici 2.05.

Vljudno vabljeni!

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Ponedeljkov fizikalni kolokvij

V ponedeljek, 14.11.2016, bo imel Andrej Studen predavanje v okviru izvolitve v naziv docenta z naslovom PET imaging with silicon sensors. Predavanje bo ob 16:15 na Fakulteti za matematiko in fiziko, Jadranska 19, predavalnica F1. Vljudno vabljeni!

Andrej Studen

 

 

 

 

ABSTRACT: Silicon seems an unlikely candidate for imaging in positron emission tomography. However, the ability to provide spatially accurate interaction positions of energetic photons can be exploited to yield significantly improved images. In the presentation, physics of PET imaging will be introduced, focusing on interplay of sensor spatial resolution and final image quality, concluded by potential application of silicon based PET imaging probes.

Predavanje: dr. ORLY ALTER (University of Utah, ZDA)

V sredo, 29.6.2016, ob 13h vljudno vabimo na predavanje dr. ORLY ALTER (Scientific Computing and Imaging Institute and the Huntsman Cancer Institute, University of Utah) z naslovom Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics. Predavanje bo potekalo v veliki predavalnici Instituta Jožef Stefan, Jamova 39, Ljubljana.

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Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics

We are developing new mathematical frameworks to do what no others currently can, that is, create a single coherent model from multiple high-dimensional datasets, known as tensors. The frameworks – comparative spectral decompositions – generalize those that underlie the theoretical description of the physical world. We are using the frameworks to compare and contrast datasets recording different aspects of a single disease, such as genomic profiles of multiple cell types from the same set of patients, measured more than once by several different methods. By using the complex structure of the datasets, rather than simplifying them as is commonly done, the frameworks enable the separation of patterns of DNA alterations – which occur only in the tumor genomes – from those that occur in the genomes of normal cells in the body, and from variations caused by experimental inconsistencies. The patterns that we uncover in the data are expected to offer answers to the open question of the relation between a tumor’s genome and a patient’s outcome. For example, recent comparisons of the genomes of tumor and normal cells from the same sets of ovarian and, separately, glioblastoma brain cancer patients uncovered patterns of DNA copy-number alterations that were found to be correlated with a patient’s survival and response to chemotherapy. For three decades prior, the best predictor of ovarian cancer survival was the tumor’s stage; more than a quarter of ovarian tumors are resistant to the platinum-based chemotherapy, the first-line treatment, yet no diagnostic existed to distinguish resistant from sensitive tumors before the treatment. For five decades prior, the best prognostic indicator of glioblastoma was the patient’s age at diagnosis. The ovarian and brain cancer data were published, but the patterns remained unknown until the team applied their comparative spectral decompositions. Pending experimental revalidation, we will bring the patterns that we uncover to the clinic, to be used in personalized diagnostic and prognostic pathology laboratory tests. The tests would predict a patient’s survival and response to therapy, and doctors could tailor treatment accordingly.

Dr. Orly Alter:

Dr. Alter is a USTAR associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah. Inventor of the “eigengene,” she pioneered the matrix and tensor modeling of large-scale molecular biological data, which, as she demonstrated, can be used to correctly predict previously unknown cellular mechanisms. Dr. Alter received her Ph.D. in applied physics at Stanford University, and her B.Sc. magna cum laude in physics at Tel Aviv University. Her Ph.D. thesis on “Quantum Measurement of a Single System,” which was published by Wiley-Interscience as a book, is recognized today as crucial to the field of gravitational wave detection.