#medicalimageanalysis resultados de búsqueda

🚨 New Publication in AI that spots errors in segmentation results automatically #MedicalImageAnalysis! 🚨 The work was led by @PeijieQ59485 and is now out in Medical Image Analysis! 👉 doi.org/10.1016/j.medi…

Medical Image Analysis with Python – AI Empowering Modern Healthcare [ By Dr Chinmoy Pal | LISTEN ENGLISH ] #MedicalImageAnalysis #PythonAI #OpenCV #PyTorch #Keras #SimpleITK #MONAI #AIinHealthcare #HealthTech #TumorDetection #XRayClassification #OrganSegmentation

Medical Image Analysis with Python – AI at the Doctor’s Side drchinmoypal.com/#language #MedicalImageAnalysis #PythonAI #OpenCV #PyTorch #Keras #SimpleITK #MONAI #AIinHealthcare #HealthTech #TumorDetection #XRayAI #OrganSegmentation #DrChinmoyPal

We look forward to welcoming you this week to the city of Leeds & @UniversityLeeds. Over 150 delegates registered from over 23 countries joining us to discuss and present their #research in #medicalimageanalysis and understanding. Programme: conferences.leeds.ac.uk/miua/ #MIUA2025

🔥 Read our Paper 📚 Precision Diagnosis of Glaucoma with VLLM Ensemble Deep Learning 🔗 mdpi.com/2076-3417/14/1… 👨‍🔬 by Soohyun Wang, Byoungkug Kim, Jiheon Kang and Doo-Seop Eom #deeplearning #medicalimageanalysis

#newpaper #DeepLearning #MedicalImageAnalysis 📚Advanced Diagnosis of Cardiac and Respiratory Diseases from Chest X-Ray Imagery Using Deep Learning Ensembles 👨‍🔬By Hemal Nakrani et al. 🔗Read the full article: mdpi.com/2224-2708/14/2… @MDPI @MDPIEngineering @JSAN_MDPI

Final opportunity to submit your work and to attend #MIUA2025 - 29th Conference on Medical Image Understanding and Analysis (MIUA 2025) is now accepting 3 page (+2 pages references) abstract. For more details: conferences.leeds.ac.uk/miua/special-s… #medicalimageanalysis #computervision

𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗶𝗺𝗮𝗴𝗲 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 is a critical field that merges healthcare with advanced computational techniques to extract meaningful insights... To know more, 𝘃𝗶𝘀𝗶𝘁: pareidolia.in/what-is-medica… 📩[email protected] | 📱+91-9230025446 . . #MedicalImageAnalysis

🫀Our latest work, Bridging multi-level gaps: Bidirectional reciprocal cycle framework for text-guided label-efficient segmentation in #echocardiography, is now published in #MedicalImageAnalysis journal. 📄 Read the full paper here: lnkd.in/eNi_6CPP #ExplainableAI #NLP

🚀 NEW PAPER OUT! 👀 doi.org/10.1016/j.medi… in #MedicalImageAnalysis ✅ CA models atrial arrhythmias efficiently ✅ Cuts AF simulation time ✅ Enables exploring more scenarios 📌 Part of @RomittiGiada's #PhD thesis

#DomainGeneralization is vital for modern #MedicalImageAnalysis, enabling models to handle diverse data from varied sources. Explore #DG techniques, the need for better benchmarks, and future research directions in @ProceedingsIEEE's Oct 2024 issue: bit.ly/MedIA-DG

Presented by #KoreaUniversity and @DukeU authors, "#DomainGeneralization for #MedicalImageAnalysis: A Review" explores DG techniques, categorizing data-level, feature-level, model-level, and analysis-level methods, offering insights to improve real-world #DL applications.

#DeepLearning has transformed #MedicalImageAnalysis, yet domain shifts between training and real-world data remain challenging. Innovative #DomainGeneralization methods offer a pathway to robust solutions, as noted in @ProceedingsIEEE's Oct 2024 issue: bit.ly/ProceedingsIEE…

Advances in #deeplearning have led to significant success in #medicalimageanalysis. This article by provides a comprehensive review of #domaingeneralization techniques and their integration into the medical image analysis workflow. bit.ly/4aanNpG

#Mzansi_AI_Ecosystem #MzansiAi_Edu Medical Image Analysis with AI Analyze medical images with computer vision and deep learning techniques! Detect diseases, segment tumors, and diagnose conditions. #MedicalImageAnalysis

Deep Learning-based Knowledge Discovery in Medical Imaging – Collection in Discover Data (Springer). We invite submissions. Deadline: 30 June 2025. Collection description and details in the link: lnkd.in/dmdmd2Tj #medicalimageanalysis #federatedlearning #fewshot

📢 Read our Highly cited papers in #SpecialIssue Advances in #MedicalImageAnalysis and #ComputerAidedDiagnosis 🔗mdpi.com/journal/applsc… 👨‍🔬 Guest Editor: Dr. Valentin Sebastian Schäfer

Happy to let you know that our journal titled “Designing Deep Neural High-Density Compression Engines for Radiology Images” has been published online in @SpringerNature Circuits, Systems, and Signal Processing. This is my first journal article. #DeepLearning #MedicalImageAnalysis

Five Ways #ComputerVision Puts a Fresh Face on #Healthcare @HealthcareGuys @marketsmarkets #MedicalImageAnalysis #ML #AI #HIPAA #FaceRecognition #PHI bit.ly/33ewGuv

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features (preprint) dx.doi.org/10.1101/2020.0… PDF i.sfu.ca/ERfgNE @IvanKlyuzhin @ArmanRahmim @anthonymlortiz @BDataScientist #DeepLearning #MedicalImageAnalysis #Radiomics

Rethinking the Approach to #ArtificialIntelligence for #MedicalImageAnalysis: The Case for #PrecisionDiagnosis James H Thrall, MD, et al. @MGHImaging ow.ly/8mmI50D3qR5 @JACRJournal #BreastCancer #Mammography #AI

Congratulations to @weina_jin (weina.me) for being selected as a recipient of Borealis AI Global Fellowship award to continue her work on Explainable AI #XAI and #DeepLearning in #MedicalImageAnalysis borealisai.com/en/blog/boreal… @SFU_CompSci

New Computer Methods and Programs in Biomedicine paper: Testing the Ability of CNNs to Learn Radiomic Features, work with @IvanKlyuzhin @ArmanRahmim et al. PDF i.sfu.ca/syBNQy DOI doi.org/10.1016/j.cmpb… #MedicalImageAnalysis #DeepLearning #MachineLearning @SFU_CompSci

ImHistNet - Learnable Image Histograms Application to Radiomics for Renal Cell Carcinoma Grading and Staging cs.sfu.ca/~hamarneh/ecop… #DeepLearning #MedicalImageAnalysis #MachineLearning #Cancer #Radiomics

We are looking for an early stage #researcher to join our team in #Rotterdam! Experience in #MedicalImageAnalysis? Check out this #vacancy!#AIradiology #MedicalImaging #MachineLearning #DeepLearning #radiology #DL #ML #Hiring #jobopening hubs.ly/H0g9SWm0

Oral presentation by @izdsaeed at SNMMI2022. Context-Aware Filtering for Direct Joint Attenuation and Scatter Correction of Whole-Body PET Images Slides: www2.cs.sfu.ca/~hamarneh/ecop… #MedicalImageAnalysis #DeepLearning #PET

New J. Medical Image Analysis paper: Guidelines and evaluation for clinical explainable AI in medical image analysis @weina_jin @XiaoxiaoLi8 @mostafa_fatehi @SFU_CompSci PDF: i.sfu.ca/Nrasje Website: weina.me/clinical_xai_g… #XAI #DeepLearning #MedicalImageAnalysis

Looking forward to putting this @nvidia RTX A6000 to good use #MedicalImageAnalysis @NVIDIAAI

Check out @__KumarAbhishek’s work on Mask2Lesion, GAN-based paired image translation approach for synthesizing skin lesion images from binary segmentation masks PDF i.sfu.ca/LUhhrR Code i.sfu.ca/fHuinm #MedicalImageAnalysis #DeepLearning #Dermatology @SFU_CompSci

Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods? arxiv.org/abs/1811.03691 #machinelearning #DeepLearning #medicalimageanalysis

📢 Read our Highly cited papers in #SpecialIssue Advances in #MedicalImageAnalysis and #ComputerAidedDiagnosis 🔗mdpi.com/journal/applsc… 👨‍🔬 Guest Editor: Dr. Valentin Sebastian Schäfer

#ISBI2021 paper with @__KumarAbhishek on Matthews correlation coefficient as a #DeepLearning loss for segmenting skin lesions PDF: i.sfu.ca/alBxoI Code: git.io/JYCJj Presentation: youtu.be/FFqjAbg_-7E #MedicalImageAnalysis #ComputerVision

Single molecule network analysis identifies structural changes to caveolae and scaffolds due to mutation of the caveolin-1 scaffolding domain nature.com/articles/s4159… rdcu.be/ciiRj #SuperResolution #Microscopy #MedicalImageAnalysis

🔥 Read our Paper 📚 Precision Diagnosis of Glaucoma with VLLM Ensemble Deep Learning 🔗 mdpi.com/2076-3417/14/1… 👨‍🔬 by Soohyun Wang, Byoungkug Kim, Jiheon Kang and Doo-Seop Eom #deeplearning #medicalimageanalysis

#DeepLearning to directly predict the clinical management of #skin lesions from images. Work with @__KumarAbhishek & @JeremyKawahara. nature.com/articles/s4159… PDF: i.sfu.ca/rpEwXM #MedicalImageAnalysis #MachineLearning #dermatology #cancer

(Preprint) Characterization of Trichome Phenotypes to Assess Maturation & Flower Development in Cannabis Sativa L. by Automatic Trichome Gland Analysis: dx.doi.org/10.2139/ssrn.4… #MedicalImageAnalysis #SFUAgritech #MedicalCannabis #DeepLearning #PrecisionAgriculture @SFU_CompSci

#IEEE_TMI paper DEEMD: Drug Efficacy Estimation against #SARSCoV2 based on cell Morphology with Deep Multiple Instance Learning PDF 📰 i.sfu.ca/yFsJPL Code 💽 i.sfu.ca/DReJKS #MedicalImageAnalysis #DeepLearning #COVID19 @SFU_CompSci @NabiRobert @LabLibbrecht