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関連する概念動画

Computed Tomography01:10

Computed Tomography

8.9K
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.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
410
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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What is an Electrochemical Gradient?01:26

What is an Electrochemical Gradient?

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Adenosine triphosphate, or ATP, is considered the primary energy source in cells. However, energy can also be stored in the electrochemical gradient of an ion across the plasma membrane, which is determined by two factors: its chemical and electrical gradients.
The chemical gradient relies on differences in the abundance of a substance on the outside versus the inside of a cell and flows from areas of high to low ion concentration. In contrast, the electrical gradient revolves around an...
128.6K
Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Network Covalent Solids02:18

Network Covalent Solids

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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
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関連する実験動画

Updated: Feb 14, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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グラディエント強化ネットワークによるコンピュータトモグラフィースキャンによるディープラーニングベースの肝臓腫瘍セグメンテーション.

Hangyeul Shin1, Kyujin Han2, Seungyoo Lee3

  • 1School of Applied Artificial Intelligence and Entrepreneurship, Handong Global University, Pohang 37554, Republic of Korea.

Diagnostics (Basel, Switzerland)
|February 13, 2026
PubMed
まとめ

この研究では,G-UNETR++ネットワークを使用して,自動化された肝臓腫瘍セグメンテーション方法を導入しています. このアプローチは,肝がんの診断を改善するための既存のモデルを上回る高精度を達成しました.

キーワード:
コンピュータートモグラフィーです.ディープラーニングとは,ディープラーニングです.グラデント強化ネットワークは,グラデント強化ネットワークです.肝臓腫瘍のセグメンテーション

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DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis
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科学分野:

  • メディカルイマージング (医学イメージング)
  • 人工知能 (AI) とは,人工知能 (AI) のことです.
  • 腫瘍学 腫瘍学

背景:

  • 肝臓腫瘍は,診断に重大な課題をもたらす.
  • 効果的な治療計画には,正確なセグメンテーションが不可欠です.
  • 既存のセグメンテーション方法は,しばしば手作業の介入を必要とします.

研究 の 目的:

  • 完全に自動化された肝臓腫瘍セグメンテーション方法を開発する.
  • グラデント強化ネットワークG-UNETR++を活用する.
  • 肝がんの診断能力を高めるために.

主な方法:

  • CTスキャンで肝臓と腫瘍のセグメンテーションにG-UNETR++を使用した.
  • 肝臓領域にセグメンテーションを集中させるためのマスキング戦略を実装しました.
  • LiTSと3DIRCADbのデータセットでモデルのトレーニングと検証を行いました.

主要な成果:

  • LiTSデータセットで平均0.844のダイススコアを達成しました.
  • 3DIRCADbのデータセットで平均0.832のダイススコアを取得しました.
  • 肝臓腫瘍のセグメンテーションにおける最先端のモデルを上回った.

結論:

  • 開発されたG-UNETR++ベースのメソッドは,効果的な自動肝臓腫瘍セグメンテーションを提供します.
  • このアプローチは,さまざまなデータセットで強い一般化性を示しています.
  • このツールは,肝臓腫瘍の診断と治療計画において医師を助けることができます.