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Phil Chlap (@PhilChlap) profile picture

Phil Chlap

@PhilChlap

Machine Learning Engineer @ Radformation. Passionate about radiation oncology research, autosegmentation/AI and open-source software.

 Austin, Texas
github.com/pchlap
Joined July 2021
  • Tweets34
  • Following112
  • Followers127
9Media
Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)Photo by Phil Chlap (@PhilChlap)
Phil Chlap retweeted
ICCR2024 (@ICCR2024) profile picture
ICCR2024@ICCR202417 Nov 2023
📢Abstract submission is now open! We’re looking forward to receiving all the exciting advancements in your research in 2-4 page paper format before January 31, 2024📅Instructions for submission are available at iccr2024.org/abstract.html📑 #ICCR2024 #CallForAbstracts #Radiotherapy
Image from ICCR2024 (@ICCR2024)
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CTV delineation quality assurance for MRI-guided prostate radiotherapy using deep learning with uncertainty estimation ⁦@Jason_Dowling⁩ ⁦@TheJamo⁩ ⁦@PhilChlap⁩ ⁦@DavePryorRO⁩ ⁦@DocJarad⁩ ⁦@InghamMedPhys⁩ thegreenjournal.com/article/…
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So proud of ⁦@VickyJChin⁩ presenting on her PhD work #ESTRO2023. Are DVH uncertainty curves the way of the future? ⁦@gerryhanna⁩ ⁦@gwalls89⁩ ⁦@ESTRO_RT⁩ ⁦@SWSLHD⁩ ⁦@swsydUNSW⁩ ⁦@InghamMedPhys⁩
Image from Shalini Vinod (@shalinivinod13)
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New publication reviewing methodological conduct of head and neck cancer (HNC) outcome prediction models. Link provides free access for 50days: authors.elsevier.com/a/1gpk~… HNC outcome prediction models containing clinical variables were reviewed 1/5
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We have a few overachievers here at Ingham Medical Physics! Check out the awesome cupcakes Rob brought in to celebrate the team's recent publication on a fully automated cardiac substructure segmentation tool. You can try it out here: pyplati.github.io/platipy/
Image from Ingham Institute Medical Physics (@InghamMedPhys)
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Celebrating our #TopCitedArticle #FreeAccess until 15 Feb 🥳 A #review of medical image data augmentation techniques for #deeplearning applications Congratulations to @PhilChlap et al #RadOnc #MedPhys @swsydUNSW @InghamMedical ow.ly/bH4H50Mxkn3
A review of medical image data augmentation techniques for deep learning applications

A review of medical image data augmentation techniques for deep learning applications

Research in artificial intelligence for radiology and radiotherapy has recently become increasingly reliant on the use of deep learning-based algorithms. While the performance of the models which...

onlinelibrary.wiley.com
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Congratulations to our fearless leader A Prof Lois Holloway on receiving the ACPSEM Distinguished Services Award that acknowledges a member who has made an outstanding contribution to the College. She is only the second woman to receive this award. @ACPSEM #EPSM #WomenWhoCurie
Image from Ingham Institute Medical Physics (@InghamMedPhys)
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Phil Chlap retweeted
JOSS (@JOSS_TheOJ) profile picture
JOSS@JOSS_TheOJ16 Oct 2022
Just published in JOSS: 'PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics applications' doi.org/10.21105/joss.04555
PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics...

PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics...

Biggs et al., (2022). PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics applications. Journal of Open Source Software, 7(78), 4555, https://doi.org...

joss.theoj.org
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Congratulations to our south west Sydney colleagues Geoff Delaney, Ian Harris, Georgie Kennedy and Tim Churches who are chief investigators on the MRFF-funded $2.6m NextCR project - to create a software framework for secure, cloud-based clinical registries buff.ly/3SEKXdR
Image from UNSW South West Sydney Clinical Campuses (@swsydUNSW)
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Early view of our latest MR distortion work is up aapm.onlinelibrary.wiley.com…
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Hot off the press: Repeatability and reproducibility of MRI-based radiomic features in rectal cancer spiedigitallibrary.org/journ… – at Sydney, New South Wales

Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal...

Purpose: Radiomics of magnetic resonance images (MRIs) in rectal cancer can non-invasively characterize tumor heterogeneity with potential to discover new imaging biomarkers. However, for radiomics to

spiedigitallibrary.org
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Check out our new publication on the technical validation of a multiparametric MRI model of glioma infiltration to guide dose painting radiotherapy doi.org/10.1016/j.phro.2022.… #CancerResearch #radiotherapy #MRI #braincancer @imagexinstitute @Sydney_Uni @InghamMedical @amsterdamumc
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Our article on MR based lung GTV delineation can now be downloaded ☺️ @shalinivinod13 @yapml @PhilChlap . #greenjournal #MDT authors.elsevier.com/a/1eVBb…
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Pleased to share our new article currently in press @RadiotherapyOn1 ⁦@shalinivinod13⁩ ⁦@mimboxer⁩⁦@yapml⁩⁦⁦@PhilChlap⁩ ⁦ We found that #MRI could be used as a comprehensive tool for lung GTV delineation! sciencedirect.com/science/ar…
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#deeplearning for volume delineation may be helpful in clinical trial QA. @TheJamo @loishol08993064 @InghamMedical @swsydUNSW Automatic radiotherapy delineation QA on prostate MRI with deep learning in a multicentre clinical trial doi.org/10.1088/1361-6560/ac… via @IOPscience
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📢 Our Artificial Intelligence Special Issue is now online! Featuring articles on #deeplearning from Chest X-rays, #AI in stroke #decisionsupport, #AI & imaging biomarkers for #radiotherapy, #distributedlearning in #radonc, & more... #MRI #CT #radiology ow.ly/1wmj50FSeYP
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