Smedby, O.
* 1997: Noise Suppression in MR Angiography Projection Images with the 3D Top-Hat Transform
* 2008: Quantitative abdominal fat estimation using MRI
* 2013: Vessel Wall Segmentation Using Implicit Models and Total Curvature Penalizers
* 2014: Automatic Multi-organ Segmentation in Non-enhanced CT Datasets Using Hierarchical Shape Priors
* 2014: Volume-Based Fabric Tensors through Lattice-Boltzmann Simulations
* 2016: Automatic Heart and Vessel Segmentation Using Random Forests and a Local Phase Guided Level Set Method
* 2016: efficient radiographic Image Retrieval system using Convolutional Neural Network, An
* 2016: Fast vascular skeleton extraction algorithm
* 2016: Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography
* 2017: Airway-Tree Segmentation in Subjects with Acute Respiratory Distress Syndrome
* 2017: Feature Space Clustering for Trabecular Bone Segmentation
* 2017: Granulometry-Based Trabecular Bone Segmentation
* 2018: Automatic brain segmentation using artificial neural networks with shape context
* 2018: Breast Cancer Histological Image Classification Using Fine-Tuned Deep Network Fusion
* 2020: Multi-Organ Nucleus Segmentation Challenge, A
Includes: Smedby, O. Smedby, Ö.[Örjan] Smedby, O.[Orjan] Smedby, Ö.
15 for Smedby, O.
Smedemark Margulies, N.[Niklas]
* 2021: Geometric Analysis of Uncertainty Sampling for Dense Neural Network Layer
* 2023: Improving adversarial robustness by learning shared information
Includes: Smedemark Margulies, N.[Niklas] Smedemark-Margulies, N.[Niklas]
Smedley, D.[David]
* 2017: Big Data and Multiple Methods for Mapping Small Reservoirs: Comparing Accuracies for Applications in Agricultural Landscapes
Smedley, K.
* 1990: Machine-Vision Applications of Image Invariants: Real-Time Processing Experiments
Smedsrud, P.H.[Pia H.]
* 2020: Kvasir-seg: A Segmented Polyp Dataset