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2004 1
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Thermal imaging of corneal transplant rejection.
Sniegowski MC, Erlanger M, Olson J. Sniegowski MC, et al. Int Ophthalmol. 2018 Dec;38(6):2335-2339. doi: 10.1007/s10792-017-0731-z. Epub 2017 Nov 4. Int Ophthalmol. 2018. PMID: 29103099
METHODS: Twenty-three eyes of twelve patients would serve as control to one eye with clinically evident corneal transplant graft rejection. A Flir T400 320 240 pixel, digital thermal camera was used to take a digital photograph and an infrared photograph of each eye. ...
METHODS: Twenty-three eyes of twelve patients would serve as control to one eye with clinically evident corneal transplant graft rejection. …
Rapid genetic screening with high quality factor metasurfaces.
Hu J, Safir F, Chang K, Dagli S, Balch HB, Abendroth JM, Dixon J, Moradifar P, Dolia V, Sahoo MK, Pinsky BA, Jeffrey SS, Lawrence M, Dionne JA. Hu J, et al. ArXiv [Preprint]. 2021 Oct 15:arXiv:2110.07862v2. ArXiv. 2021. PMID: 34671699 Free PMC article. Updated. Preprint.
We quantitatively detect complementary target sequences using DNA hybridization simultaneously for arrays of sensing elements patterned at densities of 160,000 pixels per cm$^2$. In physiological buffer, our nanoantennas exhibit average resonant quality factors of 2,200, a …
We quantitatively detect complementary target sequences using DNA hybridization simultaneously for arrays of sensing elements patterned at d …
BING: biomedical informatics pipeline for Next Generation Sequencing.
Kriseman J, Busick C, Szelinger S, Dinu V. Kriseman J, et al. J Biomed Inform. 2010 Jun;43(3):428-34. doi: 10.1016/j.jbi.2009.11.003. Epub 2009 Nov 28. J Biomed Inform. 2010. PMID: 19925883 Free article.
This manuscript introduces a biomedical informatics pipeline (BING) for the analysis of NGS data that offers several novel computational approaches to 1. image alignment, 2. signal correlation, compensation, separation, and pixel-based cluster registration, 3. signal measu …
This manuscript introduces a biomedical informatics pipeline (BING) for the analysis of NGS data that offers several novel computational app …
Improving electron micrograph signal-to-noise with an atrous convolutional encoder-decoder.
Ede JM, Beanland R. Ede JM, et al. Ultramicroscopy. 2019 Jul;202:18-25. doi: 10.1016/j.ultramic.2019.03.017. Epub 2019 Mar 26. Ultramicroscopy. 2019. PMID: 30928639
Our neural network was trained end-to-end using 512 512 micrographs created from a large dataset of high-dose ( > 2500 counts per pixel) micrographs with added Poisson noise to emulate low-dose ( 300 counts per pixel) data. ...Source code and links to our high-qu …
Our neural network was trained end-to-end using 512 512 micrographs created from a large dataset of high-dose ( > 2500 counts per pixe …
Real-time administration of indocyanine green in combination with computer vision and artificial intelligence for the identification and delineation of colorectal liver metastases.
Hardy NP, Epperlein JP, Dalli J, Robertson W, Liddy R, Aird JJ, Mulligan N, Neary PM, McEntee GP, Conneely JB, Cahill RA. Hardy NP, et al. Surg Open Sci. 2023 Mar 2;12:48-54. doi: 10.1016/j.sopen.2023.03.004. eCollection 2023 Mar. Surg Open Sci. 2023. PMID: 36936453 Free PMC article.
RESULTS: The ML algorithm correctly classified 97.2 % of CRLM ROIs (n = 132) and all benign lesion ROIs (n = 6) within 90-s of ICG administration following initial mathematical curve analysis identifying ICG inflow/outflow differentials between healthy liver and CRLMs. Time-fluor …
RESULTS: The ML algorithm correctly classified 97.2 % of CRLM ROIs (n = 132) and all benign lesion ROIs (n = 6) within 90-s of ICG administr …
An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping.
Berry JC, Fahlgren N, Pokorny AA, Bart RS, Veley KM. Berry JC, et al. PeerJ. 2018 Oct 4;6:e5727. doi: 10.7717/peerj.5727. eCollection 2018. PeerJ. 2018. PMID: 30310752 Free PMC article.
These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. ...The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique t …
These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. ...The correct …
Automatic detection and classification of hypodense hepatic lesions on contrast-enhanced venous-phase CT.
Bilello M, Gokturk SB, Desser T, Napel S, Jeffrey RB Jr, Beaulieu CF. Bilello M, et al. Med Phys. 2004 Sep;31(9):2584-93. doi: 10.1118/1.1782674. Med Phys. 2004. PMID: 15487741 Clinical Trial.
The classification algorithm operates on the focal lesions identified during detection, and includes shape-based segmentation, edge pixel weighting, and lesion texture filtering. Support vector machines are then used to perform a pair-wise lesion classification. ...
The classification algorithm operates on the focal lesions identified during detection, and includes shape-based segmentation, edge pixel …
Expected improvements in the quantitative remote sensing of optically complex waters with the use of an optically fast hyperspectral spectrometer-a modeling study.
Moses WJ, Bowles JH, Corson MR. Moses WJ, et al. Sensors (Basel). 2015 Mar 13;15(3):6152-73. doi: 10.3390/s150306152. Sensors (Basel). 2015. PMID: 25781507 Free PMC article.
With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-near-infrared spectrum, the number of pixels with negative reflectance (caused by over-correction) decreased to almost one-third, and t …
With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-ne …