A5092275244- Radiomics and Machine Learning in Medical Imaging
- Light effects on plants
- Machine Learning in Healthcare
- Photoreceptor and optogenetics research
- Explainable Artificial Intelligence (XAI)
- Graph Theory and Algorithms
- AI in cancer detection
- Health, Environment, Cognitive Aging
- Artificial Intelligence in Healthcare
- Mathematical Biology Tumor Growth
- 3D Shape Modeling and Analysis
- Glioma Diagnosis and Treatment
- Retinal Imaging and Analysis
- Molecular Communication and Nanonetworks
- Plant and Biological Electrophysiology Studies
- MRI in cancer diagnosis
- Image Processing and 3D Reconstruction
- Brain Tumor Detection and Classification
Oslo University Hospital
2023-2025
University of Oslo
2023-2024
University of Wisconsin–Madison
2020
Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology diagnosis and prognosis in neurological disorders, but its impact has been limited. This is partially attributed to the opaqueness of deep models, causing insufficient understanding what underlies their decisions. To overcome this, we trained convolutional neural networks structural brain scans differentiate dementia patients from healthy controls,...
Diffuse gliomas are malignant brain tumors that grow widespread through the brain.The complex interactions between neoplastic cells and normal tissue, as well treatment-induced changes often encountered, make glioma tumor growth modeling challenging.In this paper, we present a novel end-to-end network capable of future predictions masks multi-parametric magnetic resonance images (MRI) how will look at any time points for different treatment plans.Our approach is based on cutting-edge...
There is a broad interest in deploying deep learning-based classification algorithms to identify individuals with Alzheimer's disease (AD) from healthy controls (HC) based on neuroimaging data, such as T1-weighted Magnetic Resonance Imaging (MRI). The goal of the current study investigate whether modern, flexible architectures EfficientNet provide any performance boost over more standard architectures.
Optogenetic systems use light to precisely control and investigate cellular processes. Until recently, there had been few instruments available for applying controlled doses cultures of cells. The optoPlate, a programmable array 192 LEDs, was developed meet this need. However, LED performance varies, without calibration are substantial brightness differences between LEDs on an optoPlate. Here we present method calibrating optoPlate that uses microscope stage optical power meter automatically...
Abstract Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology diagnosis and prognosis in neurological disorders, but its impact has been limited. This is partially attributed to the opaqueness of deep models, causing insufficient understanding what underlies their decisions. To overcome this, we trained convolutional neural networks brain scans differentiate dementia patients from healthy controls,...
Longitudinal imaging allows for the study of structural changes over time. One approach to detecting such is by non-linear image registration. This introduces Multi-Session Temporal Registration (MUSTER), a novel method that facilitates longitudinal analysis in extended series medical images. MUSTER improves upon conventional pairwise registration incorporating more than two sessions recover deformations. at voxel-level challenging due effects changing contrast as well instrumental and...
Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The complex interactions between neoplastic cells and normal tissue, as well treatment-induced changes often encountered, make glioma tumor growth modeling challenging. In this paper, we present a novel end-to-end network capable of generating future masks realistic MRIs how will look at any time points for different treatment plans. Our approach is based on cutting-edge diffusion probabilistic models...
Optogenetic systems use light to precisely control and investigate cellular processes. Until recently, there had been few instruments available for applying controlled doses cultures of cells. The optoPlate, a programmable array 192 LEDs, was developed meet this need. However, LED performance varies without calibration are substantial brightness differences between LEDs on an optoPlate. Here we present method calibrating optoPlate that uses microscope stage optical power meter automatically...