Results 71 to 80 of about 758,831 (346)
Multiscale Active Contours [PDF]
, 2018 We propose a new multiscale image segmentation model, based on the active contour/snake model and the Polyakov action. The concept of scale, general issue in physics and signal processing, is introduced in the active contour model, which is a well-known ...
Bresson, Xavier +2 more
core
Interactive Segmentation in Multimodal Medical Imagery Using a Bayesian Transductive Learning Approach [PDF]
, 2009 Labeled training data in the medical domain is rare and expensive to obtain. The lack of labeled multimodal medical image data is a major obstacle for devising learning-based interactive segmentation tools.
Caban, Jesus +3 more
core +2 more sources
LEST: Large-Scale LiDAR Semantic Segmentation With Deployment-Friendly Transformer Architecture
IEEE AccessLarge-scale LiDAR-based point cloud semantic segmentation is a critical challenge for autonomous driving perception. Most state-of-the-art LiDAR semantic segmentation methods rely on complex operators, such as sparse 3D convolutions or KdTree structures,
Chuanyu Luo +6 more
doaj +1 more source
Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
International Journal of Biomedical Imaging, 2010 A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic ...
Tiffany Inglis +6 more
doaj +1 more source
Energy minimization segmentation model based on MRI images
Frontiers in Neuroscience, 2023 IntroductionMedical image segmentation is an important tool for doctors to accurately analyze the volume of brain tissue and lesions, which is important for the correct diagnosis of brain diseases.
Xiuxin Wang +7 more
doaj +1 more source
Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation [PDF]
arXiv, 2022 Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise uncertainty maps of the segmentation and allows an implicit ensemble of segmentations to boost the segmentation performance.
arxiv
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Statistical Model of Shape Moments with Active Contour Evolution for Shape Detection and Segmentation [PDF]
, 2013 This paper describes a novel method for shape representation and robust image segmentation. The proposed method combines two well known methodologies, namely, statistical shape models and active contours implemented in level set framework.
A. Foulonneau +29 more
core +3 more sources
UCP-Net: Unstructured Contour Points for Instance Segmentation [PDF]
arXiv, 2021 The goal of interactive segmentation is to assist users in producing segmentation masks as fast and as accurately as possible. Interactions have to be simple and intuitive and the number of interactions required to produce a satisfactory segmentation mask should be as low as possible.
arxiv
Molecular Oncology, EarlyView.Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane +16 more
wiley +1 more source