Search PubMedSearch

PubMed · 6375997

Estimation of sampling errors in a high-resolution TV microscope image-processing system.

Abstract

The basic postulate of this paper is that the commonly accepted sampling density of 2-4 pixels/micron in a high-resolution TV microscope system is too low to digitize exactly and analyze the complex cellular detail found in stained cell images. Depending on the specific microscope system, the required sampling density is much higher, lying between 15 and 30 pixels/micron. This sampling density is derived from the aliasing error, the resolution loss, and computational limitations. The mathematical and optical methods and equipment used to obtain these results are described in detail.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

H Harms, H M Aus. 1984. Estimation of sampling errors in a high-resolution TV microscope image-processing system.. https://doi.org/10.1002/cyto.990050303

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Analog neural nets with gaussian or other common noise distribution cannot recognize arbitrary regular languages.

We consider recurrent analog neural nets where the output of each gate is subject to gaussian noise or any other common noise distribution that is nonzero on a sufficiently large part of the state-space. We show that many regular languages cannot be recognized by networks of this type, and we give a precise characterization of languages that can be recognized. This result implies severe constraints on possibilities for constructing recurrent analog neural nets that are robust against realistic types of analog noise. On the other hand, we present a method for constructing feedforward analog neural nets that are robust with regard to analog noise of this type.

Analog-Digital Conversion

Digital images.

This tutorial introduces basic digital image processing concepts. An increasing fraction of fluoroscopic images are handled and processed using digital tools. The quality of an image in digital format depends on both the technical details of the digitization process and on the quality of the starting scene. Digital tools yield images that are difficult or impossible to achieve using analog techniques. Proper processing improves the observer's perception of clinical information.

Analog-Digital Conversion

Electrophysical factors influencing endoscopic sphincterotomy.

BACKGROUND: Analog computer techniques were used to measure electrosurgical power during sphincterotomy in experimental models and patients. METHODS: Total energy and transient changes in power were measured during sphincterotomy of bile ducts in the livers of pigs, ampullae of humans post mortem, and during clinical sphincterotomy. The effect of waveform on hemostasis was studied in experiments on canine mesenteric arteries. RESULTS: Electrosurgical waveforms (CUT, COAG, BLEND) were measured. Halving wire contact length halved energy needed to initiate cutting. The CUT waveform rarely initiated cutting at lower power settings than the BLEND waveform. With CUT, BLEND, and COAG waveforms, approximately the same energy initiated cutting. Efficiency of cutting increased linearly with power. The COAG waveform required higher power settings than BLEND or CUT to initiate cutting (p < 0.05). Force and wire diameter influenced cutting. BLEND was more effectively hemostatic than CUT (p < 0.05). COAG was significantly more hemostatic than BLEND and CUT. Cutting efficiency during clinical sphincterotomy was poor. CONCLUSIONS: This work has practical implications. Shortening wire contact length was effective in starting a cut at suboptimal settings, whereas changing from BLEND to CUT made little difference. Increasing power setting may help if cutting does not start. BLEND stops bleeding better than CUT. COAG stops bleeding better than BLEND but cuts poorly. Cutting during clinical sphincterotomy is inefficient and can be improved.

Analog-Digital Conversion