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The European Congress of Radiology 2023 took place last week in Vienna, returning to its traditional spot as a spring meeting. The congress welcomed 17,262 participants from 122 countries, an increase of 14 percent in comparison to ECR 2022. Under the watch of the magnificent golden skull which adorned the congress entrance hall, medical imaging professionals and industry leaders gathered for a meeting marked by cutting-edge science, invaluable education and unforgettable moments.
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The IHE Technical Frameworks, available for download below, are a resource for users, developers and implementers of healthcare imaging and information systems. They define specific implementations of established standards to achieve effective systems integration, facilitate appropriate sharing of medical information and support optimal patient care. Technical Framework documents are maintained regularly by the IHE Technical Committees through the identification and correction of errata.
The IHE Technical Frameworks General Introduction and Shared Appendices are shared by all of the IHE domain technical frameworks. Each technical framework volume contains links to this information where applicable. It is posted here for ease of reference.
IMPORTANT NOTE: In addition to the Technical Framework Volumes and Trial Implementation Supplements listed below, implementers should also review Final Text Change Proposals (CPs) in preparation for IHE Connectathons. An index of approved CPs is found here.
In the summer of 2022, NASA's James Webb Space Telescope released images from some of its earliest observations with the newly commissioned telescope. Almost instantaneously, these stunning images landed everywhere from the front pages of news outlets to larger-than-life displays in Times Square.
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There are two sets of labels, each associated with one of the studies. Thefirst set of labels is associated with the studypublished in Radiology and focuses on four chest x-ray findings: airspace opacity, pneumothorax,nodule/mass, and fracture. The second set of labels is associated withthe study published in Scientific Reports and includes all 14 findings released in the original dataset,and a normal/abnormal label.
In validation_labels.csv and test_labels.csv, the metadata provided as partof the NIH Chest x-ray dataset has been augmented with four columns, one for theadjudicated label for each of the four conditions: fracture, pneumothorax,airspace opacity, and nodule/mass. There are 1,962 unique image IDs in the testset and 2,412 unique image IDs in the validation set for a total of 4,374 imageswith adjudicated labels. Only YES and NO appear in the adjudication labelcolumns. If a column value is missing, then the image was not included in theadjudicated image set.
The labels are in the directory all_findings_expert_labels. Intest_individual_readers.csv, each row corresponds to a single radiologist'slabels for a single image. This means that each image ID and patient ID isrepeated across multiple rows (five rows per image, one row per reader). Eachrow also contains a reader ID so that the radiologists can be distinguished.Because there are a total of 810 images in this set,test_individual_readers.csv contains 4,050 rows with 810 unique image IDs.test_individual_readers.csv also contains a total of 19 columns. In additionto image ID, patient ID, and reader ID, there is a column for normal/abnormal, acolumn for each of the 14 findings, and a column for Other indicating otherabnormal findings are present (outside of the 14 specified). A cell value ofYES means "present" and NO means "absent".
The 2012 ACA Coot Basics can be found here. The 2012 ACA Coot Extras can be found here. The 2010 CCP4 Study weekend presentation can be found here.How do I cite Coot? Please see the FAQ. Get the paper. I like to spell Coot with a capital "C" and lower-case "oot", with italics. I am not dogmatic about it.
Mammography: A radiograph of the breast that is used for cancer detection and diagnosis. Tumors tend to appear as regular or irregular-shaped masses that are somewhat brighter than the background on the radiograph (i.e., whiter on a black background or blacker on a white background). Mammograms can also detect tiny bits of calcium, called microcalcifications, which show up as very bright specks on a mammogram. While usually benign, specific patterns of microcalcifications could indicate the presence of cancer. Learn more about mammography here.
Computed tomography (CT): Combines traditional x-ray technology with computer processing to generate a series of cross-sectional images of the body that can later be combined to form a three-dimensional x-ray image. CT images are more detailed than plain radiographs and give doctors the ability to view structures within the body from many different angles. Learn more about CT here.
Radiation therapy in cancer treatment: X-rays and other types of high-energy radiation can be used to destroy cancerous tumors and cells by damaging their DNA. The radiation dose used for treating cancer is much higher than the radiation dose used for diagnostic imaging. Therapeutic radiation can come from a machine outside of the body or from a radioactive material that is placed in the body, inside or near tumor cells, or injected into the blood stream. Learn more about radiation treatment for cancer therapy here.
Single-frame x-ray tomosynthesis (SFXT): Conventional x-ray radiography generates a single two-dimensional image, which is created by imaging a single plane at a single time point. X-ray tomosynthesis, on the other hand, uses multiple images, which are then reconstructed to generate more information, such as a three-dimensional image. Unlike CT imaging, where the source/detector physically travels at least 180 degrees around the patient, tomosynthesis uses a limited rotational angle and takes fewer images (requiring less radiation and less expense). Current tomosynthesis approaches, however, generate a static snapshot of the tissue of interest and do not allow for real-time imaging.
Imaging to guide lung biopsies: Lung cancer is the leading cause of cancer-related mortality in the United States, and analyzing lesions found in the lungs is a way to screen for the disease and to guide treatment. For a biopsy, one method to obtain lung tissue is through a bronchoscopy, where a thin tube is passed through the nose or mouth and guided into the lungs. However, obtaining tissues of interest remains difficult, as locating and visualizing such lesions is challenging. To overcome these limitations, researchers have developed a new, cost-effective chest x-ray tomosynthesis system that can generate high-resolution, real-time images of the lungs, which would allow for improved visualization during a transbrochial biopsy. In addition to being less expensive and easier to use than standard CT-based approaches, this x-ray technique is stationary and does not require any physical motion of the x-ray source or detector. Further, this method uses low doses of radiation, which would be beneficial for patients who require multiple biopsies. This x-ray system is currently being optimized for pre-clinical large animal evaluation.
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