Auto-segmentation of thoraco-abdominal organs in pediatric dynamic MRI.
Yusuf AkhtarJayaram K UdupaYubing TongTiange LiuCaiyun WuRachel KoganMostafa Al-NouryMahdie HosseiniLeihui TongSamarth MannikeriDewey OdhnerJoseph M McdonoughCarina LottAbigail ClarkPatrick J CahillJason B AnariDrew A TorigianPublished in: medRxiv : the preprint server for health sciences (2024)
Motivated by applications in surgical planning for disorders such as TIS, AIS, and EOS, we have shown an auto-segmentation system for thoraco-abdominal organs in dMRI acquisitions. This proposed setup copes with the challenges posed by low resolution, motion blur, inadequate contrast, and image intensity non-standardness quite well. We are in the process of testing its effectiveness on TIS patient dMRI data.
Keyphrases
- deep learning
- convolutional neural network
- contrast enhanced
- abdominal aortic aneurysm
- randomized controlled trial
- magnetic resonance imaging
- artificial intelligence
- magnetic resonance
- case report
- systematic review
- high intensity
- big data
- machine learning
- single molecule
- computed tomography
- diffusion weighted imaging
- high speed
- data analysis