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Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data Collection III01:05

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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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A Systematic Approach of Data Collection and Analysis in Medical Imaging Research.

Manjunath K N1, Chitra Manuel2, Govardhan Hegde1

  • 1Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.

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Systematically collecting and classifying medical image datasets, like CT colonography, simplifies radiomic feature extraction and polyp measurement. This approach enhances the efficiency of empirical testing in medical image research.

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Area of Science:

  • Medical Imaging
  • Radiomics
  • Data Science

Background:

  • Systematic medical image dataset acquisition is challenging.
  • Anatomy segmentation is crucial for radiomic feature extraction.

Purpose of the Study:

  • To segment 3D colon from CT images for polyp measurement.
  • To systematically classify and organize datasets for easier empirical testing in medical image research.

Main Methods:

  • Utilized the National Cancer Institute (NCI) The Cancer Imaging Archive (TCIA) dataset.
  • Collected 300 DICOM images from patients aged 50-80, acquired in supine and prone positions.
  • Classified datasets based on parameters of interest and validated for completeness using DICOM standards.

Main Results:

  • A systematic data collection and classification approach was established.
  • The process facilitates easier dataset selection for empirical testing.

Conclusions:

  • Systematic data collection and classification streamline medical image analysis.
  • This methodology improves the efficiency of empirical testing in medical research.