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Posts tagged #Segmentation

Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Body Charts from CT Segmentations across the Adult Lifespan: Large-scale Cross-sectional and Longitudinal Analyses https://doi.org/10.1148/ryai.250506 #segmentation #ChestRad #Liver

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Random convolutions serve as a data augmentation strategy for deep learning-based medical image segmentation models https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #ML #MachineLearning

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⚡ 2x+ efficiency, zero compromise: By integrating Soft Mixture-of-Experts, CSMoE delivers superior or comparable performance to state-of-the-art models while requiring significantly fewer FLOPs across scene #classification, #semantic #segmentation, and #image #retrieval.

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The ZOO Model is a collection of pre-trained deep learning models in ONNX format for the Qgis Deepness plugin to perform automatic object segmentation in orthophotos and satellite imagery #segmentation

qgis-plugin-deepness.readthedocs.io/en/latest/ma...

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Models of gap gene regulation and spatiotemporal dynamics of gap gene expression in WT Tribolium embryos. (C,D) HCR FISH detecting subsets of the four core gap genes (hb, Kr, mlpt, gt) in staged WT embryos (14-38 h AEL). Panel C shows expression of hb, Kr, and mlpt concurrently in the same embryos, while panel D shows mlpt and gt concurrently in the same embryos. All embryos are oriented with anterior to the left and posterior to the right.

Models of gap gene regulation and spatiotemporal dynamics of gap gene expression in WT Tribolium embryos. (C,D) HCR FISH detecting subsets of the four core gap genes (hb, Kr, mlpt, gt) in staged WT embryos (14-38 h AEL). Panel C shows expression of hb, Kr, and mlpt concurrently in the same embryos, while panel D shows mlpt and gt concurrently in the same embryos. All embryos are oriented with anterior to the left and posterior to the right.

Embryonic patterning can arise from temporal gene activation translated into space; Mahla Ahmadi & co show that #Tribolium anterior-posterior patterning follows this logic at the genetic level. doi.org/10.1242/bio....

#TemporalPatterning #Segmentation #GeneExpressionWaves

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Personalization starts with organization.
When contacts are clearly categorized,

Why tags & segmentation matter:
✔️ Send the right message to the right audience
✔️ Understand intent at a glance

Better organization → better conversations.



#Segmentation #CRM

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Modeling whole-body, CT-derived anatomic volumes to establish reference charts for the adult lifespan https://doi.org/10.1148/ryai.250506 #CT #segmentation #ML

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Turning Routine CT into Reference Values for Quantitative Radiology https://doi.org/10.1148/ryai.251130 #CT #segmentation #MachineLearning

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Reach the right person at the right time with smart segmentation.

Try it now

#MarketingTips #Segmentation #Automation

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Body Charts from CT Segmentations across the Adult Lifespan: Large-scale Cross-sectional and Longitudinal Analyses https://doi.org/10.1148/ryai.250506 #segmentation #kidney #lungs

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Review of the AI Segmentation by TerraLab plugin for QGIS
Review of the AI Segmentation by TerraLab plugin for QGIS YouTube video by Hans van der Kwast

New video: review of the AI Segmentation by #TerraLab plugin that allows smooth image segmentation in QGIS based on Meta's Segment Anything Model.

Watch it on:
📺YouTube: youtu.be/oKxh8ldYflM
📺QwastTube: videos.qwast-gis.com/w/d8RMLJzcm1...

#QGIS #GeoAI #segmentation #SAM #OpenSource #GIS

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🆓🔓 Thorson, J.C., Babcock, R. T., Fisher, J.M., Ballard, K.J., & Robin, D.A. (2025). Declination and #Segmentation in Children with Childhood #Apraxia of Speech. Languages, 10(12), 296. doi.org/10.3390/lang... #prosody #intonation 🦋 #bskySPEECHIES
@jarciuli.bsky.social 👀 @eddychwong.bsky.social 👀

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I have no #words to describe what is or isn't a word. There's no universally accepted test, rather it depends on what aspect of words you're trying to examine, if it's written or spoken, and even the language you're using.

#linguistics #language #definition #grammar #segmentation #lexicography

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Random Convolutions for Domain Generalization of Deep Learning-based Medical Image Segmentation Models https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #DeepLearning #MachineLearning

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A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation

Amaan Valiuddin, Ruud Van Sloun, Christiaan Viviers et al.

Action editor: Xuming He

https://openreview.net/forum?id=Yzf4anYwao

#segmentation #uncertainty #robust

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

MRI-derived extra-axial cerebrospinal fluid (eaCSF) reference values for children and adolescents: a tool for assessing atypical eaCSF development https://doi.org/10.1148/ryai.250123 #MRI #segmentation #AI

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Extending brain extraction tools beyond non-enhanced CT https://doi.org/10.1148/ryai.240847 #brain #segmentation #MachineLearning

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Domain generalization of medical image segmentation models with random convolutions https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #AI #MachineLearning

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

MRI-derived extra-axial cerebrospinal fluid (eaCSF) reference values for children and adolescents: a tool for assessing atypical eaCSF development https://doi.org/10.1148/ryai.250123 #NeuroRad #MRI #segmentation

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

CTA-BET outperforms five benchmark non-commercial tools in brain mask generation on non-enhanced CT and CT angiography https://doi.org/10.1148/ryai.240847 #brain #segmentation #NeuroRad

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

CTA-BET: A Robust Brain Extraction Tool for Non-enhanced CT and CT Angiography https://doi.org/10.1148/ryai.240847 #segmentation #AI #ML

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Random convolutions serve as a data augmentation strategy for deep learning-based medical image segmentation models https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #DeepLearning #ML

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Domain generalization of medical image segmentation models with random convolutions https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #AI #MachineLearning

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Solid progress today 🚀 Detection + segmentation are now wired together, assigning detected tooth numbers to segmented tooth regions. #LabelStudio #label-studio-ml-backend #ComputerVision #MedicalAI #YOLO #Segmentation

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Random convolutions serve as a data augmentation strategy for deep learning-based medical image segmentation models https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #AI #MachineLearning

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Mastering SAM Prompts: A Large-Scale Empirical Study in Segmentation Refinement for Scientific Im...

Stephen Price, Elke Rundensteiner, Danielle L. Cote

Action editor: Jianbo Jiao

https://openreview.net/forum?id=cWcTQMpqv6

#prompts #segmentation #vision

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OUTLOOK: Rewiring gene circuits to dissect oscillatory signaling dynamics
By Marek van Oostrom and Katharina Sonnen
➡️ https://genesdev.cshlp.org/content/40/1-2/1.full

Read the full story:
➡️ https://genesdev.cshlp.org/content/40/1-2/124.full

Ina Sonnen Hubrecht Institute
#optogenetic #segmentation

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

New commentary! Random convolutions for improving segmentation across different medical imaging domains https://doi.org/10.1148/ryai.251014 #segmentation #DeepLearning #MachineLearning

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RESOURCE/METHODOLOGY: Synchronization of the segmentation clock using synthetic cell–cell signaling
By Akihiro Isomura, Daisuke Asanuma, and Ryoichiro Kageyama
➡️ https://genesdev.cshlp.org/content/40/1-2/124.full

#optogenetic #signaling #segmentation #notch

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Image from article in Radiology: Artificial Intelligence

Image from article in Radiology: Artificial Intelligence

Random Convolutions for Domain Generalization of Deep Learning-based Medical Image Segmentation Models https://doi.org/10.1148/ryai.240502 @tum.de #segmentation #DeepLearning #MachineLearning

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