Keyword

automated image segmentation

Description: A computational method that automatically divides an image into meaningful regions or objects, supporting analysis in medical imaging, microscopy, and remote sensing.

Primary topic: Medical Image Segmentation Techniques (49%)

OpenAlex ID: keywords/automatic-image-segmentation

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

2016 · Sergio Pereira, Adriano Pinto, et al. · IEEE Transactions on Medical Imaging · 2,727

Automated model-based tissue classification of MR images of the brain

1999 · K. Van Leemput, F. Maes, et al. · IEEE Transactions on Medical Imaging · 1,025

Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks

2017 · Hao Dong, Guang Yang, et al. · Communications in computer and information science · 867

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Review of MRI-based Brain Tumor Image Segmentation Using Deep Learning Methods

2016 · Ali Işın, Cem Direkoğlu, et al. · Procedia Computer Science · 766

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DiameterJ: A validated open source nanofiber diameter measurement tool

2015 · Nathan A. Hotaling, Kapil Bharti, et al. · Biomaterials · 531

Automated Segmentation of MR Images of Brain Tumors

2001 · Michael R. Kaus, Simon K. Warfield, et al. · Radiology · 423

Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry

2018 · Berk Norman, Valentina Pedoia, et al. · Radiology · 419

Advances in Auto-Segmentation

2019 · Carlos E. Cardenas, Jinzhong Yang, et al. · Seminars in Radiation Oncology · 412

Fully Automatic Segmentation of Brain Tumor Images Using Support Vector Machine Classification in Combination with Hierarchical Conditional Random Field Regularization

2011 · Stefan Bauer, Lutz-P. Nolte, et al. · Lecture notes in computer science · 380

Vision 20/20: Perspectives on automated image segmentation for radiotherapy

2014 · Gregory Sharp, Karl D. Fritscher, et al. · Medical Physics · 375

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Deep-learning based, automated segmentation of macular edema in optical coherence tomography

2017 · Cecilia S. Lee, Ariel J. Tyring, et al. · Biomedical Optics Express · 361

A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images

2022 · Zhiming Cui, Yu Fang, et al. · Nature Communications · 348

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Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance

2016 · Tuan Anh Ngo, Zhi Lu, et al. · Medical Image Analysis · 332

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging

2017 · Fang Liu, Zhaoye Zhou, et al. · Magnetic Resonance in Medicine · 319

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Extensible visualization and analysis for multidimensional images using Vaa3D

2014 · Hanchuan Peng, Alessandro Bria, et al. · Nature Protocols · 314

A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images

2000 · Quan Liang, I. Wendelhag, et al. · IEEE Transactions on Medical Imaging · 311

Automated detection of retinal layer structures on optical coherence tomography images

2005 · Delia Cabrera Fernández, Harry M. Salinas, et al. · Optics Express · 288

Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images

2020 · Frank C. Setzer, Katherine J. Shi, et al. · Journal of Endodontics · 239

Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging

1992 · Ron Kikinis, Martha E. Shenton, et al. · Journal of Magnetic Resonance Imaging · 237

Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy

2013 · Kenny Kong, Christopher J. Rowlands, et al. · Proceedings of the National Academy of Sciences · 236

A state of the art review on intima–media thickness (IMT) measurement and wall segmentation techniques for carotid ultrasound

2010 · Filippo Molinari, Guang Zeng, et al. · Computer Methods and Programs in Biomedicine · 222

Machine Learning in oncology: A clinical appraisal

2020 · Renato Cuocolo, Martina Caruso, et al. · Cancer Letters · 211

Deep learning based retinal OCT segmentation

2019 · M. Pekala, N. Joshi, et al. · Computers in Biology and Medicine · 206

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The role of image registration in brain mapping

2001 · A.W. Toga, P.M. Thompson · Image and Vision Computing · 198

Object localization and border detection criteria design in edge-based image segmentation: automated learning from examples

2000 · M. Sonka, M. Brejl · IEEE Transactions on Medical Imaging · 194

Works count: 4,236

Citation count: 55,150