Xray Tech Tips

submitted by /u/seattlenostalgia [link] [comments] source https://www.reddit.com/r/Radiology/comments/ivtstm/stupidest_question_in_the_world_what_side_is_the/

I’m currently in my second year in my rad program. I love it so much, however I feel like I’m not picking up on things as quickly as the other students at my clinical site. In fact, today, my clinical instructor pulled me aside to have a conversation about how she “can’t picture me being a tech in a year”. Does anyone have any tips on how to do better? Has this happened to anyone before? submitted by /u/Stressedout-af [link] [comments] source https://www.reddit.com/r/Radiology/comments/ivh7se/stressed_out_second_year_student/

It's actually my wifes. She had surgery on her shoulder a couple of months ago (debridement, acromioplasty, minor rotator cuff tendon repair). Post surgical follow up has been interesting. The surgeon died of a drug OD before her first follow up appointment and the surgical center isn't the most responsive of places. She was also on some antibiotics about a week post-op due to an infection, but that seemed to go away. Want to make sure something isn't obtusely fucked up here. She felt (and heard) something 'tear' in the last week. She's having a lot of pain and she's tough as shit... Any help is much appreciated. ​ https://preview.redd.it/ypgju7dmk3o51.png?width=1244&format=png&auto=webp&s=bd7eb1cbe41fa45aa8c2b3ca7e8a8d28f2e47458 https://preview.redd.it/7jez6fbnk3o51.png?width=1487&format=png&auto=webp&s=406206af8b1aa93077397dc9fffedcd1fa8a1e60 https://preview.redd.it/282bvugok3o51.png?width=1457&format=png&auto=web...

submitted by /u/radiologymantra [link] [comments] source https://www.reddit.com/r/Radiology/comments/ivo0jo/the_patient_swallowed_a_needle_in_her_childhood/

submitted by /u/nostress99 [link] [comments] source https://www.reddit.com/r/Radiology/comments/ivnwcc/hello_guys_as_u_can_see_i_clearly_have_a_loss_of/

AI obviously has huge potential to improve healthcare, but I know (most) radiologists have a real problem with trusting a black box. Does anyone have any insight on any cases where an interpretable ML learning approach has been adopted to analyse images for disease diagnosis/prognosis? By interpretable, I guess I mean a non-deep learning approach, where the output can be linearly traced back to the image features so the clinician can see why the prediction was made. Or if they don't, why don't they? Just as some background info, I'm a PhD student in machine learning with radiology. In particular, we are working on cardiac MRIs. submitted by /u/twigface [link] [comments] source https://www.reddit.com/r/Radiology/comments/iv8rib/anyone_know_if_the_nhseu_use_ai_for_imagingbased/

submitted by /u/dicksledgehammer [link] [comments] source https://www.reddit.com/r/Radiology/comments/iv5z6t/pedestrian_vs_auto_not_a_good_way_to_start_your/