scholarly journals Correlative Light and Electron Microscopy of poly(ʟ-lactic acid) Spherulites for Fast Morphological Measurements using a Convolutional Neural Network

Microscopy ◽  
2021 ◽  
Author(s):  
Yuji Konyuba ◽  
Hironori Marubayashi ◽  
Tomohiro Haruta ◽  
Hiroshi Jinnai
Keyword(s):  
Neural Network ◽  
Electron Microscopy ◽  
Lactic Acid ◽  
Convolutional Neural Network ◽  
Light And Electron Microscopy

scholarly journals DeepCLEM: automated registration for correlative light and electron microscopy using deep learning

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1275
Author(s):  
Rick Seifert ◽  
Sebastian M. Markert ◽  
Sebastian Britz ◽  
Veronika Perschin ◽  
Christoph Erbacher ◽  
...  
Keyword(s):  
Neural Network ◽  
Electron Microscopy ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
High Precision ◽  
Light And Electron Microscopy ◽  
Fiducial Markers ◽  
Fluorescent Signal ◽  
Fluorescence Images ◽  
Automated Registration

In correlative light and electron microscopy (CLEM), the fluorescent images must be registered to the EM images with high precision. Due to the different contrast of EM and fluorescence images, automated correlation-based alignment is not directly possible, and registration is often done by hand using a fluorescent chromatin stain, or semi-automatically with fiducial markers. We introduce “DeepCLEM”, a fully automated CLEM registration workflow. A convolutional neural network predicts the fluorescent signal from the EM images, which is then automatically registered to the experimentally measured chromatin signal from the sample using correlation-based alignment. The complete workflow is available as a FIJI macro and could in principle be adapted for other imaging modalities as well as for 3D stacks.

scholarly journals Enhanced CNN Based Electron Microscopy Image Segmentation

2012 ◽  
Vol 12 (2) ◽  
pp. 84-97 ◽  
Author(s):  
M. Leena Silvoster ◽  
V. K. Govindan
Keyword(s):  
Neural Network ◽  
Electron Microscopy ◽  
Image Segmentation ◽  
Convolutional Neural Network ◽  
Computational Efficiency ◽  
Perceptual Grouping ◽  
High Quality ◽  
Sem Images ◽  
Neural Processes ◽  
Microscopy Image

Abstract Detecting the neural processes like axons and dendrites needs high quality SEM images. This paper proposes an approach using perceptual grouping via a graph cut and its combinations with Convolutional Neural Network (CNN) to achieve improved segmentation of SEM images. Experimental results demonstrate improved computational efficiency with linear running time.

The Morphology of Vacuolated Cells in the Liver Following Administration of Vitamin A.

1973 ◽  
Vol 31 ◽  
pp. 408-409
Author(s):  
Odell T. Minick ◽  
Hidejiro Yokoo ◽  
Fawzia Batti
Keyword(s):  
Electron Microscopy ◽  
Body Weight ◽  
Vitamin A ◽  
Light And Electron Microscopy ◽  
Liver Cells ◽  
Prominent Feature ◽  
Vascular Space ◽  
Vacuolated Cell ◽  
Vacuolated Cells ◽  
Vacuolated Cytoplasm

Vacuolated cells in the liver of young rats were studied by light and electron microscopy following the administration of vitamin A (200 units per gram of body weight). Their characteristics were compared with similar cells found in untreated animals.In rats given vitamin A, cells with vacuolated cytoplasm were a prominent feature. These cells were found mostly in a perisinusoidal location, although some appeared to be in between liver cells (Fig. 1). Electron microscopy confirmed their location in Disse's space adjacent to the sinusoid and in recesses between liver cells. Some appeared to be bordering the lumen of the sinusoid, but careful observation usually revealed a tenuous endothelial process separating the vacuolated cell from the vascular space. In appropriate sections, fenestrations in the thin endothelial processes were noted (Fig. 2, arrow).

Control of Autogenous Vein Grafts Prior to Reimplantation, By Electron Microscopy

1972 ◽  
Vol 30 ◽  
pp. 106-107
Author(s):  
John H. L. Watson ◽  
John L. Swedo ◽  
M. Vrandecic
Keyword(s):  
Electron Microscopy ◽  
Light And Electron Microscopy ◽  
Physiological Saline ◽  
Experimental Conditions ◽  
Vein Grafts ◽  
Arterial Blood ◽  
Saphenous Veins ◽  
Autogenous Vein ◽  
Control Of Parameters ◽  
Post Implantation

The ambient temperature and the nature of the storage fluids may well have significant effects upon the post-implantation behavior of venus autografts. A first step in the investigation of such effects is reported here. Experimental conditions have been set which approximate actual operating room procedures. Saphenous veins from dogs have been used as models in the experiments. After removal from the dogs the veins were kept for two hours under four different experimental conditions, viz at either 4°C or 23°C in either physiological saline or whole canine arterial blood. At the end of the two hours they were prepared for light and electron microscopy. Since no obvious changes or damage could be seen in the veins by light microscopy, even with the advantage of tissue specific stains, it was essential that the control of parameters for successful grafts be set by electron microscopy.

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