The columnar organization of the second synaptic region of the visual system of Musca domestica L.

1972 ◽  
Vol 124 (4) ◽  
pp. 561-585 ◽  
Author(s):  
J. A. Campos-Ortega ◽  
N. J. Strausfeld
2008 ◽  
Vol 509 (4) ◽  
pp. 422-435 ◽  
Author(s):  
Katarzyna Miśkiewicz ◽  
Friedrich-Wilhelm Schürmann ◽  
Elżbieta Pyza

2020 ◽  
Author(s):  
Samson Chengetanai ◽  
Adhil Bhagwandin ◽  
Mads F. Bertelsen ◽  
Therese Hård ◽  
Patrick R. Hof ◽  
...  

Author(s):  
W. L. Steffens ◽  
Nancy B. Roberts ◽  
J. M. Bowen

The canine heartworm is a common and serious nematode parasite of domestic dogs in many parts of the world. Although nematode neuroanatomy is fairly well documented, the emphasis has been on sensory anatomy and primarily in free-living soil species and ascarids. Lee and Miller reported on the muscular anatomy in the heartworm, but provided little insight into the peripheral nervous system or myoneural relationships. The classical fine-structural description of nematode muscle innervation is Rosenbluth's earlier work in Ascaris. Since the pharmacological effects of some nematacides currently being developed are neuromuscular in nature, a better understanding of heartworm myoneural anatomy, particularly in reference to the synaptic region is warranted.


Author(s):  
Klaus-Ruediger Peters

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.


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