84 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Tel Aviv UniversityIL14 papers
- Hebrew University of JerusalemIL6 papers
- University College LondonGB3 papers
- Academic College of Tel Aviv-YafoIL2 papers
- Bar-Ilan UniversityIL2 papers
- Children's Hospital of Eastern OntarioCA2 papers
- Harvard UniversityUS2 papers
- Johns Hopkins MedicineUS2 papers
- Johns Hopkins UniversityUS2 papers
- National Institute on AgingUS2 papers
- National Institutes of HealthUS2 papers
- Rush University Medical CenterUS2 papers
15 papers
A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometry
Chiara Di Vece, Zhehua Mao, Netanell Avisdris +7
Accurate fetal growth assessment from ultrasound (US) relies on precise biometry measured by manually identifying anatomical landmarks in standard planes. Manual landmarking is tim…
X-ray2CTPA: Leveraging Diffusion Models to Enhance Pulmonary Embolism Classification
Noa Cahan, Eyal Klang, Galit Aviram +4
Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detai…
Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM)
Liad Doniza, Mitchel Lee, Tamar Blumenfeld Katzir +5
Quantitative Susceptibility Mapping (QSM) is a technique for measuring magnetic susceptibility of tissues, aiding in the detection of pathologies like traumatic brain injury and mu…
Partial annotations for the segmentation of large structures with low annotation cost
Bella Specktor Fadida, Daphna Link Sourani, Liat Ben Sira Elka Miller +2
Deep learning methods have been shown to be effective for the automatic segmentation of structures and pathologies in medical imaging. However, they require large annotated dataset…
Automatic fetal fat quantification from MRI
Netanell Avisdris, Aviad Rabinowich, Daniel Fridkin +9
Normal fetal adipose tissue (AT) development is essential for perinatal well-being. AT, or simply fat, stores energy in the form of lipids. Malnourishment may result in excessive o…
BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes
Netanell Avisdris, Leo Joskowicz, Brian Dromey +5
Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometr…
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…
Learning Personal Representations from fMRIby Predicting Neurofeedback Performance
Jhonathan Osin, Lior Wolf, Guy Gurevitch +5
We present a deep neural network method for learning a personal representation for individuals that are performing a self neuromodulation task, guided by functional MRI (fMRI). Thi…
Automatic linear measurements of the fetal brain on MRI with deep neural networks
Netanell Avisdris, Bossmat Yehuda, Ori Ben-Zvi +6
Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal b…
Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer's Disease
Rahul Ghosal, Vijay R. Varma, Dmitri Volfson +4
Wearable data is a rich source of information that can provide deeper understanding of links between human behaviours and human health. Existing modelling approaches use wearable d…
Distributional data analysis via quantile functions and its application to modelling digital biomarkers of gait in Alzheimer's Disease
Rahul Ghosal, Vijay R. Varma, Dmitri Volfson +5
With the advent of continuous health monitoring with wearable devices, users now generate their unique streams of continuous data such as minute-level step counts or heartbeats. Su…
K-shell decomposition reveals hierarchical cortical organization of the human brain
Nir Lahav, Baruch Ksherim, Eti Ben-Simon +3
In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the d…
Reference-Based MRI
Lior Weizman, Yonina C. Eldar, Dafna Ben-Basaht
Purpose: In many clinical MRI scenarios, existing imaging information can be used to significantly shorten acquisition time or to improve Signal to Noise Ratio (SNR). In this paper…
Compressed sensing for longitudinal MRI: An adaptive-weighted approach
Lior Weizman, Yonina C. Eldar, Dafna Ben Bashat
Purpose: Repeated brain MRI scans are performed in many clinical scenarios, such as follow up of patients with tumors and therapy response assessment. In this paper, the authors sh…
Levels of Complexity in Scale-Invariant Neural Signals
Plamen Ch. Ivanov, Jeffrey M. Hausdorff, S. Havlin +5
Many physical and physiological signals exhibit complex scale-invariant features characterized by scaling and long-range power-law correlations, suggesting a possibly common…