ECTS Credits Participation in the summer school will give 3 ECTS points provided that one attends all lectures, perform all exercises, and presents a poster that is prepared in advance. To actually get the ECTS credits, you should register for the course as described here.
Poster Presentations If you want to bring a poster you must:
- Bring a poster. Ideally the poster should present your research interest in a way that can be understood by fellow students and colleagues that are not domain specialist. It should be the basis of a good discussion. It does not need to be within the topic of the summer school.
- The poster should be no larger than A0 in portrait mode (88cm wide x 126cm tall).
- Send a PDF version of your poster to the poster-responsible: William Michael Laprade willap@dtu.dk (Billy) latest August 1st.
- Create one or two brief slides (powerpoint, PDF, etc) that can be used as a poster pitch. Send your slides to Billy latest August 5th.
- Pitch your poster at the poster session Monday evening. The pitch is a 1 minute presentation. The time limit is strict!
- Present your poster at the poster session.
Poster printing If you are travelling from abroad or if it is very complicated for you to print a poster, then let Billy know and we can print it for you.
Poster pitch order
Maximum poster pitch time is 1 minute – 30 seconds even better.
- Albert Alonso – Fast detection of slender bodies in high density microscopy data
- Alejandro Uribe – Longitudinal Self-Supervised Deep Learning for Image-guided Radiotherapy
- Amanda Amissah – Phenotyping Seed Shattering of Perennial Ryegrass
- Ana-Teodora Radutoiu – Automated estimation of cardiac stroke volumes from computed tomography
- Andreas Aspe – Utilising AI on Computed Tomography for 3D Vertebral Segmentation and Fracture Detection
- Anna Anikina – Eye-tracking for assessing X-rays image interpretation
- Asbjørn Munk – AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation
- Athanasios Delatolas – What I have been doing the past year
- Athanasios Oikonomou – Object detection and quantitative analysis of PFSs on diverse 2D and 3D biological systems using semi-supervised models
- August Høeg – Expanding the context of Volumetric Super-Resolution via Multi-Scale Transformers
- Bjørn Hansen – Synthesis of Medical Images
- Bjørn Møller – Finding NEM-U
- Changlu Guo – Channel Attention Separable Convolution Network for Skin Lesion Segmentation
- Chun Kit Wong – Deploying Deep Learning Model in Real World Clinical Setting: a case study in obstetric ultrasound
- Dovile Juodelyte – Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging
- Emily Sørensen – Direct Observation and Kinetic Quantification of Stochastic Protein-Protein Interactions at the Single-Molecule Level
- Frederik Johansen – Deep Generative Models for Characterising Atomic Structures of Nanomaterials
- Hazrat Bilal – Optimized KiU-Net: Lightweight Convolutional Neural Network for Retinal Vessel Segmentation in Medical Images
- Hui Zhang – Predicting urban tree cover from incomplete point labels and limited background information
- Jakob Ambsdorf – Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models
- Jakob Christensen – Universal Image Segmentation with Diffusion Models
- Julia Machnio – Deep Learning Based Localization and Characterization of White Matter Lesions
- Julie Boel & Katja Norsker – AI-Driven Outlier Detection Of The Human Vertebra From Computed Tomography
- Kristin Engel – Advanced diffusion-weighted magnetic resonance spectroscopy data acquisition and processing
- Mahsa Kalashami – Improving Cardiovascular Diagnostics with AI through Analyzing MRI Scans for Coronary Artery Disease
- Maia Ekstrand – Mitochondrial Dynamics and Motility Impact Islet Hormone Secretion and are Regulated Differently in Alpha and Beta Cells
- Manxi Lin – Incorporating Clinical Guidelines through Adapting Multi-modal Large Language Model for Prostate Cancer PI-RADS Scoring
- Maria Montgomery – Prediction of Breast Cancer Risk in Women Aged 40-50 Using BERT-Based Model
- Mathias Lowes – Implicit Neural Representations for Registration of Left Ventricle Myocardium During a Cardiac Cycle
- Mia Siemon – Video Anomaly Detection Simplified
- Michele Rocca – Policy-Space Diffusion for Physics-Based Character Animation
- Nina Weng – Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation
- Pawel Pieta – Structural analysis of mozzarella cheese
- Peter Kampen – Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLP
- Reza Karimzadeh – Search in free-text radiology report database using large language model cooperation
- Ruiqi Cui – Synthesis of Geometric Models for Axons
- Sebastian Loeschcke – LoQT: Low Rank Adapters for Quantized Pre-Training
- Sebastiano Marinelli – Protoporphyrin fluorescence quantification in glioblastoma tumor phantoms
- Sheyla Ballestero – 3D Whole-heart fibrosis: Can we quantify it?
- Sophia Bardenfleth – Superresolution of real-world multiscale bone CT verified with clinical bone measures
- Sumit Pandey – Validating YOLOv8 and SAM Foundation Models for Robust Point-of-Care Ultrasound Segmentation
- Thea Brüsch – FreqRISE: Explaining time series using frequency masking
- Thor Christiansen – Quad mesh generation using Reinforcement Learning
- Ulrik Friis-Jensen – Using Deep Generative Models for Atomic Structure Prediction of Metal Oxide Nanoparticles from X-ray Scattering Data
- Venkanna Guthula – Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment
- William Laprade – Masked Autoencoders for Hyperspectral Imaging
- Yogita Yogita – Combining Physics and Deep Learning: A New Framework for Image Denoising
- Zahra Sobhaninia – Fetal Ultrasound Image Segmentation for Measuring Biometric Parameters Using Multi-Task Deep Learning