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At least 739 records · Page 41Linked to original sources
PubMed1994

A computerized image analysis system for estimating Tanner-Whitehouse 2 bone age.

A method for assigning Tanner-Whitehouse 2 skeletal maturity scores (or bone ages) to hand-wrist X-rays by an image analysis computer system is described. An operator positions the relevant area of the X-ray on a light box beneath a video camera. Correct positioning is assured by computer templates of each bone stage. Thereafter the process is automatic; the computer, not the operator, rates the bones. The system produces continuous stage scores, not discrete ones such as B, C or D. Data are given which show that the computer-assisted skeletal age score is more repeatable than the usual manual (or unassisted) rating. The absolute difference between duplicates averaged 0.25 stages; differences of as much as 1.0 stage occurred in only 3% of duplicates compared with 15% obtained in manual ratings.

Age Determination by Skeleton↗
PubMed1999

Artificial neural network-aided image analysis system for cell counting.

BACKGROUND: In histological preparations containing debris and synthetic materials, it is difficult to automate cell counting using standard image analysis tools, i.e., systems that rely on boundary contours, histogram thresholding, etc. In an attempt to mimic manual cell recognition, an automated cell counter was constructed using a combination of artificial intelligence and standard image analysis methods. METHODS: Artificial neural network (ANN) methods were applied on digitized microscopy fields without pre-ANN feature extraction. A three-layer feed-forward network with extensive weight sharing in the first hidden layer was employed and trained on 1,830 examples using the error back-propagation algorithm on a Power Macintosh 7300/180 desktop computer. The optimal number of hidden neurons was determined and the trained system was validated by comparison with blinded human counts. System performance at 50x and lO0x magnification was evaluated. RESULTS: The correlation index at 100x magnification neared person-to-person variability, while 50x magnification was not useful. The system was approximately six times faster than an experienced human. CONCLUSIONS: ANN-based automated cell counting in noisy histological preparations is feasible. Consistent histology and computer power are crucial for system performance. The system provides several benefits, such as speed of analysis and consistency, and frees up personnel for other tasks.

Cell Count↗
PubMed1986

Guidelines for selecting a dietary analysis system.

Microcomputers provide an effective and efficient method for dietary data management and analysis. Since the selection of an appropriate software system is a confusing task, prospective users must have a clear statement of needs. Selection of software is simplified when specific data management tasks are defined. This article provides a model for listing dietary analysis needs and priorities. Sample dietary analysis tasks are listed for five areas of responsibility. Prospective users should consider the following characteristics for each system: validity of the data base, soundness of the program's internal operating procedures, clear and complete documentation, an easy-to-read computer output, and credibility of the developer. Characteristics that may vary in importance depending on the user's situation include ability to alter the data base, standard operating procedures, output features, and service policies. By looking carefully at needs and matching needs to available systems, dietitians can apply sophisticated dietary data management and analysis techniques to the nutrition needs of their clients.

Computers↗
PubMed2002

Feasibility of using a video-based motion analysis system for measuring thumb kinematics.

While several different methods have been used to measure hand kinematics, fluoroscopy is generally considered to be the most accurate. Recently, video-based motion analysis has been developed for the measurement of joint kinematics. This method is versatile, easy to use, and can measure motions dynamically. Surface markers are most commonly used in the video-based motion systems. However, whether the surface markers placed on the thumb accurately represent the true kinematics of the underlying bony segment is questionable. In this study, the feasibility of surface markers to represent thumb kinematics was investigated by fluoroscopy. Both the positions of surface markers and bony landmarks were simultaneous recorded and then digitized. The Ra(2) values comparing the angular changes of the thumb interphalangeal, metacarpal and carpometacarpal joints derived using the surface markers or bony landmarks were 0.9986, 0.9730 and 0.9186 in the flexion/extension plane respectively, 0.8837, 0.9697 and 0.8775 in the abduction/adduction plane; and 0.9884, 0.9643 and 0.9431 in the opposition plane. The ranges, mean and standard deviation of the absolute differences between calculated angles of different marker sets were also compared. These data revealed that the similarities of the two different marker techniques throughout the motion cycle were high. The differences between the two methods were also within clinically allowable range of +/-5 degrees. It is concluded that the application of the video-based motion analysis system with surface markers to thumb kinematics is warranted.

Adult↗
PubMedDate not supplied

Developing a computer program to assist the nursing process: phase I-from systems analysis to an expandable program.

In a three-stage project, a computer program was devised to assist in the nursing process. As Stage I, a definition of nursing was developed upon which a systems model of the nursing process was constructed. In Stage II, the computer program was written to collect patient data and formulate nursing diagnoses related to functions of the skin, mucous membranes, nails, and hair. The program was designed to serve as a model for the development of a more comprehensive program that would include other functional areas, suggest patient objectives and nurse interventions, and help to evaluate nursing care. In Stage III, initial trials were conducted to obtain feedback from nurses. Nurses found the program took too long but agreed that with modification it could help them give better care.

Computers↗