🌟 Proud to be the author of Chapter 7 in the newly published Artificial Intelligence Applications for Brain-Computer Interfaces (Elsevier). Grateful for the support from @hessovalais & @_TheSense_ . Thanks to the editors! 📚 Now available: https://t.co/fdcl9DQpBh

🎉My research on ML for early Alzheimer's & MCI diagnosis via brain MRI, supervised by Prof. @jpcik, is published in Discover Applied Sciences! Grateful for the support of @Swiss_FCS, @_TheSense_ , @hessovalais, @unil, & @CHUVLausanne. 📚Read here: https://t.co/eX3EvU4yji

The most fun image & video creation tool in the world is here. Try it for free in the Grok App.

🌟Completed 1-yr Research Fellowship at @hessovalais. Grateful to the Swiss Gov. Excellence Scholarship #ESKAS & @unil for this opportunity. A huge thank you to my supervisor Prof. @jpcik, and special thanks to Profs Henning Müller, @adepeursinge, and Michael Ignaz Schumacher.

🚀 Early Alzheimer’s diagnosis with Machine Learning! 🧠 Our research, led by @HeliaGivian & @jpcik, reviews 10 years of progress using MRI images to improve diagnosis. 📰 https://t.co/kvB0FOOM6F @hessovalais #Alzheimers #MachineLearning #Healthcare

🧠🌟Thrilled to share our review on ML approaches for diagnosing Alzheimer's and MCI based on brain MRI, now published! Grateful for the guidance from @jpcik & @_TheSense_ , and support from @Swiss_FCS, @hessovalais @unil, and @CHUVLausanne. Paper link: https://t.co/x2RXzjgxWY

🌟Honored to share my interview with @hessovalais about my life and career goals! 🌟 Huge thanks to “Anne Darbellay” for the engaging conversation. Grateful for this opportunity! #HesSoValaisWallis #MedicalAnalysis #UniversityofLausanne #MedicalResearch #MedicalEngineering

🦠🩻Comparative Qualitative Analysis of COVID-19 vs. Non-COVID-19 CT Scans The image processing based on AI algorithms and Avizo software has been conducted and is shown below. Raw data: The Cancer Imaging Archive database (TCIA) #ImageAnalysis #AI #Radiology #MedicalResearch

Excited to share my gratitude for the recent workshop "9th AI Valais/Wallis" organized by @hessovalais @Idiap_ch. It was an great experience learning about "Artificial Intelligence and Human-AI Teaming". Huge thanks to presentors and organizer for their expertise and guidance!

🌟AI-Days-2024🌟: In this event, cutting-edge technologies in terms of AI and the application of AI in different fields have been provided. I would like to extend my sincere gratitude to all professors and the entire organizing committee for orchestrating such a successful event.

👩‍🔬📊The 2D and 3D quantitative and qualitative analysis were applied to T1-weighted MRI to segment the ocular structures. I performed the image analysis using MATLAB programming and conducted 3D segmentation automatically using the Avizo software. Raw Data: ADNI #AI #MRI #optic

The "Workshop on Computational Methods for Neurovascular Imaging”. A big thanks to the organizers/speakers for sharing valuable knowledge. Special thanks to Professors; @TranslationalML, @mckinley_scan, and @MRITobi for giving me this opportunity to have a conversation with them

Thank you to everyone who supported me during my life and career. I’m thrilled that I have been selected as a main candidate in the Swiss Government Excellent Scholarship for the Research Fellowship at the HES-SO University Valais Wallis. #HESSO#TheSense#AISLab#UNIL#CHUV#ML#DL

The role of 18F-FDG PET in neurodegenerative disorder imaging. In this post, PET scans of a normal person and a person with Alzheimer’s disease have been analysed and shown bellow. Raw data: Alzheimer’s Disease Neuroimaging Initiative (ADNI) #ImageAnalysis #PET #Alzheimers

Image processing of Alzheimer’s disease brain tissue using MATLAB and ImageJ to segmentation of tau protein and neurons. Increasing tau protein buildup (brown spots) and fewer neurons (red) in people with AD in comparison with healthy people. Raw data: Grinberg lab/UCSF

The analysis were applied to non-small cell lung cancer in order to calculate tumor volume using advanced image processing. The analyzed 2D and 3D rendering CT scans have been shown and the segmented tumor is indicated with red color. Raw data: The Cancer Imaging Archive (TCIA)

The image segmentation process based on AI was applied on the 2D slices of T1-weighted MRI for 9 patients with three kinds of brain tumors: meningioma, glioma, and pituitary in three different views (axial, sagittal and coronal). Raw data: Figshare website #ImageAnalysis #AI