Medical Image Super-resolution/Translation Warning!
This video presents a warning about using medical image super-resolution/translation for general diagnostic purposes. Hallucination can be harmful in this situation.
References:
Distribution Matching Losses Can Hallucinate Features in Medical Image Translation, 2018
https://arxiv.org/abs/1805.08841
Audio credit:
Erik Satie: Gymnopedie No 2 by Kevin MacLeod (CC-A)
Scary Piano Hit Sound Effect by Tyops (CC-A)
Видео Medical Image Super-resolution/Translation Warning! канала Joseph Paul Cohen PhD
References:
Distribution Matching Losses Can Hallucinate Features in Medical Image Translation, 2018
https://arxiv.org/abs/1805.08841
Audio credit:
Erik Satie: Gymnopedie No 2 by Kevin MacLeod (CC-A)
Scary Piano Hit Sound Effect by Tyops (CC-A)
Видео Medical Image Super-resolution/Translation Warning! канала Joseph Paul Cohen PhD
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
ML for Medical Text and EHR - Medical concept representation learning series
BlindTool V2 Kickstarter Video
Intro to Chester the AI Radiology Assistant
Unimodal Probability Distributions for Deep Ordinal Classification - Long
Chester the AI Radiology Assistant (V3)
Renegade Duckiebot
TorchXRayVision: A library of chest X-ray datasets and models
Sealion Counting with count-ception
Crater Detection Via Sliding Window
Medical Imaging Tutorial 2020 - Ch5 - GANs in Medical Imaging
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation
Gifsplanation via Latent Shift Talk - MIDL2021
Mona Lisa visualized by 200 random neural networks in color
Chester the AI Radiology Assistant - TensorFlow Mini Conference at Mila
ICML-UDL 2020 - A Benchmark of Medical Out of Distribution Detection
Unimodal Probability Distributions for Deep Ordinal Classification - Short
The Effect of Counterfactuals on Reading Chest X-rays. XAI4CV 2023 Presentation
What is Academic Torrents?
Academic Torrents - How to upload for researchers
Medical Imaging Tutorial 2020 - Ch4 - Incorrect Feature Attribution