ArticleIEEE transactions on medical imaging2016
Efficient Small Blob Detection Based on Local Convexity, Intensity and Shape Information.
Article in IEEE transactions on medical imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Imaging the later-life white matter pathologies of repetitive head impacts: A novel pattern revealed through T2 FLAIR MRI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Distinguishing a Drone from Birds Based on Trajectory Movement and Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- AutoGlom: software tool for segmentation and analysis of magnetic resonance images of the kidney.American journal of physiology. Renal physiology · 2026Article
- BlobCUT: A Contrastive Learning Method to Support Small Blob Detection in Medical Imaging.Bioengineering (Basel, Switzerland) · 2023Article
- Pantograph Detection Algorithm with Complex Background and External Disturbances.Sensors (Basel, Switzerland) · 2022Article
- Comparative Dissemination of Aerosol and Splatter Using Suction Device during Ultrasonic Scaling: A Pilot Study.Dentistry journal · 2022Article
- Small Blob Detector Using Bi-Threshold Constrained Adaptive Scales.IEEE transactions on bio-medical engineering · 2021Article
- Image analysis techniques to map pyramids, pyramid structure, glomerular distribution, and pathology in the intact human kidney from 3-D MRI.American journal of physiology. Renal physiology · 2021Article
- Nephron number and its determinants: a 2020 update.Pediatric nephrology (Berlin, Germany) · 2021Article
- Improved small blob detection in 3D images using jointly constrained deep learning and Hessian analysis.Scientific reports · 2020Article
- In vivo measurements of kidney glomerular number and size in healthy and OsAmerican journal of physiology. Renal physiology · 2019Article
- A New Local Fractional Entropy-Based Model for Kidney MRI Image Enhancement.Entropy (Basel, Switzerland) · 2018Article
- The Hessian Blob Algorithm: Precise Particle Detection in Atomic Force Microscopy Imagery.Scientific reports · 2018Article
- MRI tools for assessment of microstructure and nephron function of the kidney.American journal of physiology. Renal physiology · 2016Review
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8 authors.
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Abstract
The identification of small structures (blobs) from medical images to quantify clinically relevant features, such as size and shape, is important in many medical applications. One particular application explored here is the automated detection of kidney glomeruli after targeted contrast enhancement and magnetic resonance imaging. We propose a computationally efficient algorithm, termed the Hessian-based Difference of Gaussians (HDoG), to segment small blobs (e.g., glomeruli from kidney) from 3D medical images based on local convexity, intensity and shape information. The image is first smoothed and pre-segmented into small blob candidate regions based on local convexity. Two novel 3D regional features (regional blobness and regional flatness) are then extracted from the candidate regions. Together with regional intensity, the three features are used in an unsupervised learning algorithm for auto post-pruning. HDoG is first validated in a 2D form and compared with other three blob detectors from literature, which are generally for 2D images only. To test the detectability of blobs from 3D images, 240 sets of simulated images are rendered for scenarios mimicking the renal nephron distribution observed in contrast-enhanced, 3D MRI. The results show a satisfactory performance of HDoG in detecting large numbers of small blobs. Two sets of real kidney 3D MR images (6 rats, 3 human) are then used to validate the applicability of HDoG for glomeruli detection. By comparing MRI to stereological measurements, we verify that HDoG is a robust and efficient unsupervised technique for 3D blobs segmentation.
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