ArticleJournal of biomedical optics2013
Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography.
Article in Journal of biomedical optics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.
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Who cites it
98 citing papers in PubMed, 190 citations in OpenAlex.
- Visual Semantic Encoding and Identification of Naturalistic Movies via High-Density Diffuse Optical Tomography.bioRxiv : the preprint server for biology · 2025Article
- Feasibility of diffuse Raman spectroscopy to detect in-vivo molecular changes in the tissue induced by subcutaneous implants.Biomedical optics express · 2025Article
- Resorbable optical fibers for interstitial photodynamic therapy-assessment of photosensitizer spatial distribution in tumors.Journal of biomedical optics · 2025Article
- Minimum spectral resolution for continuous-wave hyperspectral near-infrared tissue spectroscopy.Journal of biomedical optics · 2025Article
- NIRSTORM: a Brainstorm extension dedicated to functional near-infrared spectroscopy data analysis, advanced 3D reconstructions, and optimal probe design.Neurophotonics · 2025Article
- The effect of adipose tissue on transdermal monochromatic light presented to the human fetus using Monte Carlo simulations.Scientific reports · 2025Article
- US & MR/CT Image Fusion with Markerless Skin Registration: A Proof of Concept.Journal of imaging informatics in medicine · 2025Article
- Fundamental effects of array density and modulation frequency on image quality of diffuse optical tomography.Medical physics · 2025Article
- Ultra high density imaging arrays in diffuse optical tomography for human brain mapping improve image quality and decoding performance.Scientific reports · 2025Article
- Two-stage diffuse fluorescence tomography for monitoring of drug distribution in photodynamic therapy of tumors.Journal of biomedical optics · 2025Article
- Functional brain mapping using whole-head very high-density diffuse optical tomography.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Sensitivity analysis of transabdominal fetal pulse oximetry using MRI-based simulations.Biomedical optics express · 2024Article
- Hybrid heterogeneous phantoms for biomedical applications: a demonstration to dosimetry validation.Biomedical optics express · 2024Article
- Evaluating feasibility of functional near-infrared spectroscopy in dolphins.Journal of biomedical optics · 2023Article
- Brain space image reconstruction of functional near-infrared spectroscopy using a Bayesian adaptive fused sparse overlapping group lasso model.Neurophotonics · 2023Article
- Optimizing a two-layer method for hybrid diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy cerebral measurements in adults.Neurophotonics · 2023Article
- Selfrec-Net: self-supervised deep learning approach for the reconstruction of Cherenkov-excited luminescence scanned tomography.Biomedical optics express · 2023Article
- Optical imaging and spectroscopy for the study of the human brain: status report.Neurophotonics · 2022Article
- Bioluminescence tomography reconstruction in conjunction with an organ probability map as an anatomical reference.Biomedical optics express · 2022Article
- Quantitative Bioluminescence Tomography for In Vivo Volumetric-Guided Radiotherapy.Methods in molecular biology (Clifton, N.J.) · 2022Article
38 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.