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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Vesicular Tubular Clusters01:45

Vesicular Tubular Clusters

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After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
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Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

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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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Computed Tomography (CT) scan:
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Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

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Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
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As used in a healthcare facility, sterilization destroys all microorganisms through physical or chemical methods. The physical method includes steam, dry heat, boiling water, and radiation.
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T2-STIR MRIにおける自動リンパ浮腫セグメンテーション：教師なしクラスタリング法を用いた

Maurizio Cè1, Marius Chiriac2, Alberto Cabri3

  • 1Radiology Department, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Via Francesco Sforza 35, 20122, Milano, Italy.

La Radiologia medica
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まとめ

教師なし人工知能（AI）法は、リンパ浮腫のためのT2-STIR MRLにおける体液セグメンテーションを自動化する。このAIツールは、リンパ浮腫および脂肪リンパ浮腫の進行の客観的な評価とモニタリングを支援する。

キーワード:
人工知能浮腫セグメンテーションk平均法クラスタリングリンパ浮腫MRIリンパ管造影教師なし学習

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科学分野:

  • 医用画像
  • 人工知能
  • 定量的解析

背景:

  • リンパ浮腫および脂肪リンパ浮腫の評価は、しばしば画像検査の主観的な解釈に依存します。
  • 浮腫の体積と分布の正確な定量化は、効果的な管理のために重要です。

研究 の 目的:

  • T2-STIR MRLにおける体液の自動セグメンテーションのための教師なしAI法の開発と検証。
  • リンパ浮腫および脂肪リンパ浮腫患者における浮腫の定量的評価。

主な方法:

  • リンパ浮腫または脂肪リンパ浮腫を有する20人の患者の後ろ向き分析。
  • 画像セグメンテーションのためのk平均法クラスタリングアルゴリズム、ダイス類似係数を用いて最適化。
  • パフォーマンス評価と3D分析のためのテストセットへの転移学習の適用。

主要な成果:

  • AIモデルは、トレーニングセットで少なくとも0.8のダイス類似係数を達成しました。
  • モデルは、テストセット（ダイススコア0.74 ± 0.05）で手動セグメンテーションとの良好な一致を示しました。
  • 視覚化には、浮腫の分布と縦断的追跡のためのカラーマップと積み重ね線グラフが含まれていました。

結論:

  • 教師なしAI法は、T2-STIR MRLにおける自動的で客観的な浮腫セグメンテーションと定量化の可能性を示しています。
  • このアプローチは、リンパ浮腫および脂肪リンパ浮腫の診断、病期分類、および治療モニタリングを支援できます。