Finally, this is out.
nature.com/articles/s4159…
Congratulations to Quincy A. Hathaway Partho P Sengupta Naveena Yanamala

🥁 Thrilled to share our work titled `RadRotator`, a #Diffusion model for rotating radiographs in 3D space with maximal user control! 🩻

Last year we released `Mediffusion`, the backbone of our #GenerativeAI work!

Check it out to train your own👇🏻

github.com/BardiaKh/Medif…

Our event is now on the #MICCAI2024 site! Explore TGI3 and other great satellite events! #MedicalImaging
#Topology - and #Graph -Informed #Imaging Informatics #Geometry
Xiaoling Hu Quincy A. Hathaway Chao Chen

With an estimated annual incidence of one million patients in the U.S. and affecting approximately 26 million patients worldwide, heart failure is on the rise. bit.ly/48A2V8L Quincy A. Hathaway Penn Radiology Penn Radiology Residents Johns Hopkins Radiology

#WVUgame

Excited to share the first published work from my collaborations with the Demehri Lab at Johns Hopkins. #AI #ComputerVision #Pectoralis #CT #HeartFailure #Radiology RSNA Radiology: Cardiothoracic Imaging

doi.org/10.1148/ryct.2…

Check out our article on #cardioonc and Covid infection with intermediate term follow up. Data comes from one of the largest Covid registry N3C NIH link.springer.com/article/10.118…
Dr. George Sokos Scott Chapman Diego Sadler MD FACC Sherry-Ann Brown, MD, PhD, FACC, FAHA Daniel Addison, MD Tochi Okwuosa #GlobalHealth #CardioOnc

New insights on leveraging Geometry to enhance Convolutional Neural Networks in Medical Imaging!
More: sciencedirect.com/science/articl…

Is the US radiology residency match getting MORE or LESS competitive⁉️

Join Arya H. Mirzaian & Enis C. Yilmaz, MD for an in-depth dive into multi-decade trends in #RadRes match by Francis Deng, MD & Linda Moy, uncovering key insights! 📊@Radiology_RSNA Rad In Training Editor

A #RadInTraining #TWEETORIAL

If you are an interested medical student, please feel free to join us for the Annual WVU Radiology Welcome Picnic on Sunday, September 10th! #wvuradres #radres

A Curtain-raiser to the Changing Face of Cardiology Rutgers RWJMedSchool Robert Wood Johnson University Hospital Here are five #women leaders joining us in 2023 to spearhead the division's mission! A transforming, changing culture for an academic flagship RWJBarnabas -one of the many announcements to follow this year

@khosravi_bardia Radiology: Artificial Intelligence Yashbir Singh, ME, PhD Quincy A. Hathaway @FarrellyData Matthew Markert 🧠/acc Rahul @tinku09_11 Shael Brown 1. #Radiomics mainly concentrates on pulling out a vast number of features from radiological images, including shape, texture, and intensity. It's all about revealing disease characteristics not easily seen by the human eye. #RadAIchat

Radiology: Artificial Intelligence Potential diagnostic tools for clinicians, new era of quantitative life science students & researchers in academia :) #RadAIchat

Radiology: Artificial Intelligence #RadAIchat

In the field of neuroimaging, TDA can help uncover complex patterns and structures in brain imaging data, offering insights into neurological disorders like Alzheimer's, Parkinson's, and multiple sclerosis.

nature.com/articles/s4146…

Radiology: Artificial Intelligence As the amount of data increases (due to digitization, more studies, generative AI, etc) in terms of quantity and dimension, the need for efficient ways of finding patterns in data increases, TDA could be a potential solution in conjunction with other methods! #RadAIchat

Radiology: Artificial Intelligence I suppose like any other data science field, collecting and preparing raw data to make it TDA-ready is also challenging.

#RadAIChat

Radiology: Artificial Intelligence #RadAIchat
TDA's complexity poses challenges in understanding and applying it effectively. Comprehensive training and education are essential for healthcare professionals, like radiologists, to gain the necessary skills and knowledge for utilizing TDA in their work.

Radiology: Artificial Intelligence #RadAIchat
Algorithmic Bias: Like all AI technologies, TDA could potentially introduce biases if the training data does not represent the population it serves. Ensuring diverse and representative training datasets can help mitigate this bias.

Radiology: Artificial Intelligence Honestly, I think the emphasis on AI in radiology sometimes leads to underestimating the power of other data science methodologies, including TDA. The first step to bridge this gap might be to promote TDA concepts and applications in less-technical language.
#RadAIChat

Check out this paper for a great intro to TDA for neuroscientists ncbi.nlm.nih.gov/pmc/articles/P… #RadAIchat #TDA #neuroimaging