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Electron Microscope Tomography and Single-particle Reconstruction

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

Computed Tomography

Computed Tomography

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...

Imaging Studies III: Computed Tomography

Imaging Studies III: Computed Tomography

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...

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Training-free CryoET Tomogram Segmentation.

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Updated: Feb 24, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

CryoSAM：基盤モデルを用いたトレーニングフリーのクライオETトモグラムセグメンテーション

Yizhou Zhao¹, Hengwei Bian¹, Michael Mu¹

¹Carnegie Mellon University, Pittsburgh PA 15213, USA.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|February 23, 2026

まとめ

CryoSAMは、CryoET画像解析のためのトレーニング不要な新しいフレームワークを提供し、広範な手動アノテーションなしで粒子ピッキングとセグメンテーションの精度を大幅に向上させます。この進歩は、自動化された特徴識別における基盤モデルの活用により、構造生物学ワークフローを合理化します。

キーワード:

クライオ電子線トモグラフィー (CryoET)基盤モデルプロンプトベースセグメンテーション

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Leveraging Virtual Reality for Immersive Segmentation and Analysis of Cryo-Electron Tomography Data

Leveraging Virtual Reality for Immersive Segmentation and Analysis of Cryo-Electron Tomography Data

Published on: January 24, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

関連する実験動画

Last Updated: Feb 24, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Leveraging Virtual Reality for Immersive Segmentation and Analysis of Cryo-Electron Tomography Data

Leveraging Virtual Reality for Immersive Segmentation and Analysis of Cryo-Electron Tomography Data

Published on: January 24, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022