Recent Posts


Select Category

Gordon Lecture: Machine Learning for Real-time High-quality Biomedical Imaging

07/19/2019


Leslie Ying is currently a Professor of Biomedical Engineering and Electrical Engineering at the University at Buffalo, SUNY. She received her B.E. in Electronics Engineering from Tsinghua University, China in 1997 and both her M.S. and Ph.D. in Electrical Engineering from the University of Illinois at Urbana - Champaign in 1999 and 2003, respectively.
Below is a summary of her presentation

Machine learning has recently attracted a lot of attention in biomedical imaging. It has shown success in biomedical image classifications but only very recently been used for image reconstruction with unique features. For this talk, Dr. Ying started with compressed sensing (CS), a strategy for reconstruction from sub-Nyquist sampled data. Several machine-learning-based methods were introduced within the conventional CS framework. She then explained how the optimization algorithm underlying CS can be unrolled to a deep artificial neural network, such that parameters and prior models can be learned from training samples. Finally, end-to-end convolutional neural networks were presented based on the training data with little knowledge of the imaging system. Connections among different networks were discussed with their benefits and limitations highlighted. Although most examples provided were from MRI, the frameworks are generalizable to image reconstruction problems for most imaging modalities. The talk concluded with future outlooks.

Gordon Lecture: Learn Deeply to Advance Medical Imaging: Artificial Intelligence in MR and PET/MR


Dr. Fang Liu is an assistant scientist at the University of Wisconsin School of Medicine and Public Health.  Dr. Liu obtained his Ph.D. in 2015 from Medical Physics at the University of Wisconsin and completed two years of postdoctoral training at the Radiology department. Dr. Liu has extensive research experience in the technical development of MR imaging for MR pulse sequence design, image reconstruction, quantitative imaging, and image analysis.
Below is a summary of his presentation

Medical imaging is a research field that remains plenty of technical and clinical challenges. The recent development of Artificial Intelligence, particularly Deep Learning (DL), has demonstrated high potentials to resolve such challenges. Dr. Liu presented some of his recent work for DL theory development and applications in medical imaging and will discuss the performance, strengths, and limitations. The talk gave an overview of DL in medical imaging and discuss some recent DL applications that successfully translate new learning-based approaches into performance improvement in MR and PET/MR imaging workflow.  One primary aim is to draw tightly connections between fundamental DL concepts and clinically relevant challenges in medical imaging. Topics covered rapid MR image acquisition, reconstruction and MR quantitative mapping, and image post-processing such as image segmentation and synthesis in MR and PET/MR, and finally lead to DL augmented disease diagnosis and prediction. The talk concluded with a discussion of open problems in DL that are particularly relevant to medical imaging and the potential challenges and opportunities in this emerging field.

Gordon Lecture: Broadband Photon Tomography

06/28/2019


Prof. Frederik J. Beekman Ph.D. heads the section Radiation, Detection & Medical Imaging at TU Delft University. He co-authored over 150 journal papers and is the inventor on 31 patents. His research interests includes biomedical imaging science, AI and image guided radio(-nuclide) therapy.  He is an associate editor of several journals and founder and CEO/CSO of MILabs (www.milabs.com) that develops and markets high performance biomedical imaging systems.
Below is a summary of his presentation

High Performance Integrated 4x4D PET, SPECT, Optical & X-ray Tomography

In preclinical research scientists have dreamed about a 3D magnifying glass that would allow us to e.g. see various cell functions and structures in a dynamic 4D single scan, and map integrated detailed dynamics of e.g. contrast agents, tracers, pharmaceuticals, receptors and indicators of therapy response in tumours. To meet these and many other imaging needs Dr. Beekman and his lab developed the user friendly fully integrated VECTor-6 imaging platform (WMIC innovation of the Year 2018) comprising:In preclinical research scientists have dreamed about a 3D magnifying glass that would allow us to e.g. see various cell functions and structures in a dynamic 4D single scan, and map integrated detailed dynamics of e.g. contrast agents, tracers, pharmaceuticals, receptors and indicators of therapy response in tumours. To meet these and many other imaging needs Dr. Beekman and his lab developed the user friendly fully integrated VECTor-6 imaging platform (WMIC innovation of the Year 2018) comprising:

A) down to ~0.1 mm SPECT & 0.55 mm PET resolution, with positron-range free PET for otherwise “difficult isotopes” like 124I, 76Br, 86Y, and 82Rb.  B) concurrent sub-mm multi-tracer PET & PET-SPECT  C) sub-second dynamic PET & SPECT  D) sub-mm resolution imaging of α & β-emitting pharmaceuticals,  E)  ultra-high performance low dose X-ray CT and  F) optical tomography (Cherenkov, Fluorescence & Bioluminescence)

In this presentation this highly adaptive and versatile nuclear, optical and structural imaging platform was explained along with many scientific applications contributed by hundreds of worldwide users. Finally, the results of translating their nuclear imaging technologies into <3 mm resolution clinical SPECT (G-SPECT, WMIS Innovation of the Year 2015) was presented.

Gordon Lecture: Radiopharmaceutical Therapy: History, Current Status and Future Potential

06/04/2019


Bennett S. Greenspan, M.D., M.S. received his M.D. degree from the University of Illinois in Chicago. He completed residencies in Diagnostic Radiology and Nuclear Medicine and is certified in Diagnostic Radiology and Nuclear Radiology by the ABR and in Nuclear Medicine by the ABNM. He received the M.S. degree in medical physics from UCLA. Dr. Greenspan is devoted to teaching of clinical nuclear medicine and also physics and radiation safety of nuclear medicine to nuclear medicine and radiology residents.  He is also keenly interested in quality and safety in Nuclear Medicine.
Below is a summary of his presentation

History - Radiopharmaceutical therapy began in 1941 with the efforts and insight of Saul Hertz, MD of MGH and also Arthur Roberts, PhD of MIT. From that beginning, I-131 has become an important agent for the treatment of benign and malignant thyroid disease. In the 1980s, two agents, Sr-89 chloride and Sm-153 EDTMP, were introduced for bone pain palliation. Somatostatin receptor targeted therapies were developed in the 1980s and 1990s, leading to FDA-approval of Lu-177 Dotatate in 2018. Radiolabeled antibodies were also being developed in the 1970s – 2000s, with the introduction of two agents in 2002 and 2003. Radium-223 dichloride was approved by the FDA in 2013 for treatment of castrate-resistant metastatic prostate cancer.

Read more...

Gordon Lecture: Preoperative and Intraoperative Localization for Pulmonary nodule


Dr. Hyun Koo Kim is Professor and Chief of Thoracic and Cardiovascular Surgery at the Korea University Guro Hospital in Seoul, Korea. He earned his medical degree from Korea University College of Medicine in Seoul Korea in 1996. He finished a Thoracic and Cardiovascular Surgery residency in 2001 and afterwards completed a fellowship in the Korea University Guro Hospital in 2005. He is an expertise in single port VATS and utilizing 3D thoracoscope during VATS.
Below is a summary of his presentation

Image-guided surgery can be defined as surgery where the operator utilizes surgical devices that incorporate the use of tracking technology in conjunction with a fusion of images in order to guide surgical procedures. 

Preoperative marking via CT-guided localization is the most commonly used techniques for thoracoscopic surgery-based resection of small peripheral pulmonary nodules. But, it was related with resulting in higher rates of pneumothorax, bleeding, and dislodgement.Preoperative marking via CT-guided localization is the most commonly used techniques for thoracoscopic surgery-based resection of small peripheral pulmonary nodules. But, it was related with resulting in higher rates of pneumothorax, bleeding, and dislodgement.

Read more...

Gordon Lecture: Advanced MRIs in CNS

05/20/2019


Dr. Meiyun Wang is a neuroradiologist, Professor and Chair of the Medical Imaging Center of Henan Province and Chair of the Department of Radiology of Henan Provincial People’s Hospital. She received her M.D. from Southeast University in 1995, a PhD from Capital University of Medical Sciences in 2005, and then worked as a post-doctoral research fellow at the Massachusetts General Hospital, Harvard Medical School from 2006-2008. She became the Vice-Chair in 2008 Chair in 2016 of the Department of Radiology of Henan Provincial People’s Hospital in China.
Below is a summary of her presentation.

In this talk, the applications of three non-contrast enhanced advanced MR techniques, including Diffusion Kurtosis Imaging (DKI), Strategically Acquired Gradient Echo (STAGE) and a Length and Offset Varied Saturation (LOVARS) in central nervous system (CNS) were summarized.

DKI has been used to measure non-Gaussian diffusion, which has the potential to characterize both normal and pathologic tissue better than diffusion-tensor imaging. Some previous researchers have suggested that DKI might provide more accurate information about water diffusion. Dr. Wang's study showed that mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

STAGE is an advanced Susceptibility weighted imaging (SWI) which can provide multi-contrast images in one scan, such as T1W, PDW, T1 MAP, PD MAP, R2* MAP, SWI, and even MRA images in 5 minutes. It is very helpful in early detecting and evaluating ischemia, brain trauma and some other CNS diseases.

Read more...

Gordon Lecture Series: Learning reconstruction and analysis for medical imaging

05/13/2019


Dr. Shanshan Wang is an associate professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. She received her dual Ph.D degree from the University of Sydney and Shanghai Jiaotong University respectively in information technologies and biomedical engineering. Dr. Wang was a finalist for the Australian John Makepeace Bennett Best Thesis Award and won the 2018 OCSMRM Outstanding Research Award. Her research interests include machine learning, fast medical imaging and biomedical signal analysis.
Below is a summary of her presentation

Inverse problems are ubiquitous in the field of medical imaging and image processing. Prominent examples include fast MR imaging and image denoising. The goal of these problems is to reconstruct or restore an unknown image from a set of direct/indirect measurements. However, due to the limitation of the acquisition time or the existence of noise, the obtained measurements are often corrupted or incomplete, which introduces big challenges for the reconstruction process and the following clinical diagnosis. In order to remove the noise or overcome the ill-posed nature caused by the insufficient measurements, it is necessary to explore the prior knowledge and utilize them to form constraints in the reconstruction process so as to make up for the missing or corrupted information.

Read more...
Dr. Kwon

Gordon Lecture: Activatable Molecular Probes for Optical Imaging

05/06/2019


Dr. Ick Chan Kwon is a Presidential Scholar at KIST-DFCI On-Site-Lab in Department of Cancer Biology, Dana Farber Cancer Institute Boston. He is a Tenured Principal Research Scientist of Korea Institute of Science and Technology (KIST). He received his B.S. and M.S. degrees in College of Engineering at Seoul National University and his Ph. D. in Pharmaceutics and Pharmaceutical Chemistry from University of Utah. After a post-doctoral training at CCCD in University of Utah, he joined KIST where he started his research on polymeric nanoparticle-based drug delivery system for antibiotics, anticancer drugs and gene therapy. He also pioneered in a research filed of Theragnosis, by combining molecular imaging and drug delivery system with smart nano-probes. He is a fellow of The Korean Academy of Science & Technology and a member of The National Academy of Engineering of Korea.
Below is a summary of his presentation

Dr. Kwon

For decades, molecular imaging which can monitor inter-/intracellular functions or molecular processes in an organism has provided valuable information for various research fields. Biomarkers such as enzymes, receptors and proteins can be utilized as a target of molecular imaging since they can provide information for early diagnosis and monitoring therapeutic effect of diseases. Among them, receptor-ligand interaction based molecular imaging technique has been emerging promising strategy in theragnosis of intractable diseases such as cancer.
In this talk, Dr. Kwon introduced epidermal growth factor receptor (EGFR) and CD 47 receptor-specific self-quenched imaging probes, which can emit fluorescence (activate) via de-quenching reaction in lysosome. His talk also included a simple noninvasive labeling and tracking technique for cell therapeutics via combination of metabolic glycoengineering and biootherogonal copper-free click chemistry, resulting in the cells being tracked via near-infrared fluorescence (NIRF), magnetic resonance (MR) and computed tomography (CT) imaging without cytotoxicity and functional interference.