Life

On Washington’s Birthday also known as President’s Day, on February 18, 2019, I attended the George Washington Birthday Parade in Alexandria, VA, and the day before I visited the National Portrait Gallery, which is a part of the Smithsonian Institution, in Washington D.C. The George Washington Birthday Parade marches through Old Town Alexandria and is billed as the largest George Washington Birthday Parade in the U.S. While at the National Portrait Gallery I visited the Hall of Presidents which has portraits of nearly all American presidents. Below are some pictures I took while over Presidents’ Day weekend in February, 2019.

Ulysses_Grant_president_portrait
Abraham_Lincoln_president_portrait
Andrew_Jackson_president_portrait
Washington_Parade_Old_Town_start
Washington_Parade_Alexandria_police_motorcycles
George_Washington_Parade_Alexandria_Virginia
Washington_Parade_Alexandria_cannon
Washington_Parade_Alexandria_Marching_Band
Washington_Parade_Old_Town_motorcycles
George_Washington_Parade_Alexandria_bagpipes
Washington_Parade_Alexandria_politicians
Washington_Parade_Alexandria_firetrucks
Washington_Parade_Alexandria_Virginia_guns
Washington_Parade_Alexandria_costumes
Washington_Parade_Alexandria_Virginia_gunfire
Washington_Parade_Alexandria_flags
ngton_Parade_Alexandria_horse_carriage
Washington_Parade_Alexandria_dummer_boy
Washington_Parade_Alexandria_Ben_Franklin
Washington_Parade_Alexandria_treasurer
Washington_Parade_Alexandria_war_jeep
Presidents_Day_Parade_Alexandria_Virginia_bagpipes
Washington_Parade_Alexandria_go-kart
Washington_Parade_Alexandria_American_flag

For the pictures taken from the National Portrait Gallery, the Smithsonian permits still and video photography for noncommercial use only in its museums and exhibitions, unless otherwise posted, as indicated at https://www.si.edu/visit/security. All images above from inside the museums of the Smithsonian Institution are being used for noncommericial purposes. Refer to the disclaimer http://www.toddmccollough.com/policy-disclaimer/for additional policies of this site.

I am pleased that a paper titled “A Phase Shift and Sum Method for UWB Radar Imaging in Dispersive Media” has been published in IEEE Transactions on Microwave Theory and Techniques, in 2019, that I am a co-author on through prior work with the Celadon Research Division of Ellumen Inc.

This paper discusses applying a novel algorithm called phase shift and sum (PSAS) algorithm to reconstruct images from data collected from a fully automatic frequency and time domain measurement system for microwave imaging using a pair of movable antennas. The system described in the paper incorporates features from the Microwave Imaging Device patent where a pair of movable antennas are independently controlled to rotate around a region of interest. This paper builds upon work previously presented in 2018, in IEEE Transactions on Microwave Theory and Techniques in the paper A Time-Domain Measurement System for UWB Microwave Imaging and in 2017, in Progress In Electromagnetic Research C in the paper A novel cavity backed monopole antenna with UWB unidirectional radiation.

waveform sine - A Phase Shift and Sum Method for UWB Radar Imaging in Dispersive Media
This image is from pixabay

The PSAS algorithm resolves the multispeed and multipath issue when UWB signals propagate in dispersive media. In the PSAS method, frequency components in the UWB scattered signal are individually processed for phase shift compensation and amplitude decay compensation. The phase shift frequency responses are integrated over the spectrum, and the results are converted to a pixel value at each focal point to form an image. Using time domain signals collected from a digital phosphor oscilloscope for experimental tests, PSAS is compared to two traditional time-shift radar-based microwave imaging algorithms: delay-multiply-and-sum (DMAS) and robust artifact resistant (RAR). In the experimental tests two different objects are placed in a plastic graduated cylinder filled with glycerin. Results demonstrate superiority of PSAS over traditional time-shift methods with the lowest possibility of missing a weak scatterer and the lowest possibility of distortion of an object. I encourage you to download and read the full “A Phase Shift and Sum Method for UWB Radar Imaging in Dispersive Media” paper from IEEE for all the details of the algorithm, experimental setup, and image reconstruction results.

I visited the National Christmas Tree outside of the White House and also the U. S. Capitol Christmas Tree in Washington, D. C. in 2018. I was able to see both of the Christmas Trees with their lighting turned on at night as I visited after the National Christmas Tree Lighting was held on November 28, 2018, and the U. S. Capitol Christmas Tree Lighting was held on December 6, 2018. Both the National Christmas Trees and the U. S. Capitol Christmas Tree have their own websites where you can find out more information. I also visited the National Christmas Tree shortly before dark to better see the National Christmas Tree Railroad and train display underneath. Below are some pictures I took of both of the Christmas Trees.

National_Christmas_Tree_White_House
National_Christmas_Tree_2018
National_Christmas_Tree_Washington_DC
National_Christmas_Tree_2018_unlit
National_Christmas_Tree_Train
US_Capitol_Christmas_Tree_2018
US_Capitol_Christmas_Tree_waterfront

I was able to attend the Radiological Society of North America’s (RSNA) 104th Scientific Assembly and Annual Meeting at McCormick Place in Chicago, IL, which occurred from November 25 to November 30, 2018. The annual meeting is a very large gathering of industry leaders in medical imaging, radiologists, and other related industry professionals. This was the 104th Scientific Assembly and Annual Meeting with the tagline: Tomorrow’s Radiology today. This year brought back much emphasis on machine learning and 3D printing. As usual there were many exhibitors with new medical imaging devices ready to discuss and provide demonstrations. In particular there were a few 1st time exhibitors I was excited to see including EMTensor and Butterfly Network. There was also a U.S. market debut by United Imaging Healthcare which had a large exhibitor space. As usual there were also numerous posters and presentations.

This year brought back the popular deep learning classroom presented by the NVIDIA Deep Learning Institute (DLI) designed for attendees to engage with deep learning tools, write algorithms and improve their understanding of deep learning technology. In one session, called Introduction to Deep Learning, attendees used convolutional neural networks (CNNs) along with a MedNIST data set that consists of 1,000 images each from 5 different categories: Chest X-ray, hand X-ray, Head CT, Chest CT, Abdomen CT, and Breast MRI. The task was for the attendees to identify the image type. Another session focused on 3D segmentation of Brain MR using deep learning methods for segmentation, particularly V-nets.

This year also brought back the machine learning showcase which allowed for the opportunity to network with nearly 80 companies on the forefront of the developments in machine learning and artificial intelligence. This year introduced a new showcase called the 3D printing & advanced visualization showcase which focused on groundbreaking technology in 3D printing, virtual reality and augmented reality. Another new feature this year was a Recruiters Row which allow for attendees to connect with organizations offering career opportunities. Like last year there was also a start-up showcase that featured emerging companies bringing innovations in medical imaging.

I was able to attend a few educational courses and scientific sessions. In particular I attended a session titled Image Processing in Imaging and Radiation Therapy and another session titled Deep Learning in Radiology: How Do We Do It? In the former session I was intrigued by the talk from ImBio which trained a CNN to create quality ventricle segmentations with only 43 scans in the training dataset and used data augmentations to improve the performance on the test dataset and another talk from researchers at the University of Chicago to classify chest radiographs as anteroposterior or posteroanterior. The latter session as indicated above I attended featured insights into deep learning in radiology at The Ohio State University, Stanford University, and the Mayo Clinic Rochester.

Below are some of the pictures I took while at the RSNA annual meeting in 2018, in Chicago, IL.

RSNA_2018_Welcome

RSNA_2018_Sign

RSNA_2018_Lobby

RSNA_2018_Posters

RSNA_Nvidia_Deep_Learning

RSNA_Ask_Expert_Media_Production

RSNA_McCormick_Place_Lobby

RSNA_Samsung_Imaging

RSNA_Varex_Imaging_CT

RSNA_United_Imaging

RSNA_Siemens_Healthineers

RSNA_2018_EMTensor_device

RSNA_2018_EMTensor_banner

RSNA_3D_Printing_Advanced_Visualization_Showcase_Presentations

RSNA_3D_SYSTEMS

RSNA_Canon_Computed_Tompgraphy

RSNA_Materialise_Booth

materialise_3D_printing_RSNA

RSNA_Zebra_medical_vision

RSNA_NVIDIA_Booth

RSNA_mindray

RSNA_GE_SIGNA_Premier

RSNA_Hitachi_Computed_Tomography

RSNA_Machine_Learning_Showcase_Presentations

RSNA_Philips_ultrasound

RSNA_Butterfly_Network

RSNA_IBM_Watson_Health

RSNA_Hologic

RSNA_Corporate_Partners_2018

I also attended last years RSNA annual meeting in 2017 which you can find more information and photos at here http://www.toddmccollough.com/radiological-society-north-america-rsna-chicago-il-2017-mccormick-place/.

On September 30, 2018, I visited the National Zoological Park of the Smithsonian Institution in Washington D.C. The National Zoo features exhibits of many different animals including gorillas, orangutans, lions, tigers, cheetahs, zebras, red river hogs, scimitar-horned oryx, alligators, crocodiles, turtles, american bison, elephants, seals, beavers, porcupines and giant pandas. Below are some pictures taken at the National Zoo in Washington D.C.

National_Zoo_Tiger

National_Zoo_Female_Lion

National_Zoo_Male_Lion

National_Zoo_Tiger

National_Zoo_Turtle

National_Zoo_Alligator

National_Zoo_Tortoise

National_Zoo_Gorilla

National_Zoo_Animal

National_Zoo_Armadillo

National_Zoo_Elephants

National_Zoo_Washington_DC_Elephant_Pool

National_Zoo_Panda_Habitat

National_Zoo_Giant_Panda

National_Zoo_American_Bison

National_Zoo_Zebra

National_Zoo_Cheetah

National_Zoo_Red_River_Hog

National_Zoo_scimitar_horned_oryx

Washington_DC_Zoo_Elephant

National_Zoo_Beaver

National_Zoo_Seal

National_Zoo_Crocodile

National_Zoo_Porcupine

National_Zoo_Smithsonian_Sign

National_Zoological_Park_Washington_DC_Smithsonian