Overview

Residents, fellows, radiologic technologists, physics students, and medical students are invited to submit images or video clips for placement on the RSNA-ACR public information Web site, RadiologyInfo.org, for a chance to win a $100 Amazon.com gift card.

If you wish to submit, first determine the specific page of RadiologyInfo.org where the image or video clip belongs.

Members of the RSNA-ACR Public Information Web Site Committee will review the submissions to determine acceptable images for posting on the Web site. An e-mail will be sent acknowledging each accepted image. Images accepted for posting will go into a pool from which three winners will be chosen quarterly. Three contest winners each quarter will receive $100 Amazon.com gift cards; winners will be notified via e-mail.

All contributors of accepted submissions will be recognized on the RadiologyInfo.org Outstanding Image Contest Page; the quarterly winners' names will also be highlighted in contest promotions and communications.

Submission Requirements

• All patient identifier information must be removed from your entry, including the file name.
• Entries may be of normal anatomy or diseases, but not cases that are unusual. Remember, these images are intended for the public. Photos and schematic drawings of radiology equipment may also be submitted, however, equipment logos and brand names should not be visible.
• Only one file can be submitted per entry. Maximum file size is 10MB.
• File names with spaces or special characters like quotation marks, apostrophes, commas, etc. cannot be uploaded. If you attempt to upload such a file, a message will display stating that the file name includes unacceptable characters. We suggest you check the file name beforehand and rename it if necessary.
• Images must be 72 to 600 dpi (300 dpi preferred) in jpg, jpeg, gif or bmp formats. Recommended width for images is 450 to 800px.
• When appropriate, images should be annotated to indicate the important findings. Images with annotations should include only arrows and/or alpha-numeric callouts (no words). The arrows and callouts should be sized to be readable when image is resized to 450px wide. Definitions for the arrows and/or callouts should be included in the caption (see example 2).
• Each entry must include a short caption describing what the image demonstrates. A text box for entering the image description is provided on the entry form.
• Video clips must be avi, wmv, or mpg, mpeg, or mp4 formats.
• Each entry must include the page where you recommend it be placed. A list of eligible pages is provided on the entry form.

Terms

• By submitting an entry you certify that the material submitted is your original work and is not copyrighted unless you are the sole owner of the copyright.
• By submitting an entry you understand and agree that material submitted may be published on the ACR-RSNA RadiologyInfo.org public Web site. You also grant permission to ACR and RSNA to edit the image and/or caption as they deem necessary.
• By submitting an entry you certify that all patient identifier information has been removed from the image or video.

I have read and agree to the terms.

How to Enter

Press the "Enter Contest" button (below) to fill out the entry form. When the form is completed, press the "Next" button and you will be prompted to upload your image.

Note: If you should need to contact someone about an entry that was submitted, please email the RadiologyInfo.org Webmaster. Include your Entry ID number in the email message. (The Entry ID number will be sent to you in a confirmation message when you submit your image.)

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Examples:

1. An image to be placed on the Bone X-ray page.	Caption: Plain film radiographic (x-ray) image (anterior-posterior view) of a normal right foot.
2. An image with annotations to be placed on the Abdominal Ultrasound page.	Caption: Gallbladder and common bile duct. a. common bile duct b. gallbladder
3. A video clip to be placed on the Abdominal CT page.	Please upgrade to the latest version of Adobe Flash Player. Click here to upgrade now. Caption: 3D modeling of CT (computed tomography) images of a cancer patient's abdomen.