Electronic Resource
A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions
| العنوان: | A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions |
|---|---|
| المؤلفون: | Ministerio de Ciencia, Innovación y Universidades (España), de Isidro-Gómez, F P, Vilas, J L, Losana, P, Carazo, J M, Sorzano, Carlos Óscar S. |
| بيانات النشر: | Elsevier 2024-03 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a very general context, including cellular in situ observations. The approach starts by collecting a set of images at different projection directions by tilting the specimen stage inside the microscope. Therefore, a crucial preliminary step is to precisely define the acquisition geometry by aligning all the tilt images to a common reference. Errors introduced in this step will lead to the appearance of artifacts in the tomographic reconstruction, rendering them unsuitable for the sample study. Focusing on fiducial-based acquisition strategies, this work proposes a deep-learning algorithm to detect misalignment artifacts in tomographic reconstructions by analyzing the characteristics of these fiducial markers in the tomogram. In addition, we propose an algorithm designed to detect fiducial markers in the tomogram with which to feed the classification algorithm in case the alignment algorithm does not provide the location of the markers. This open-source software is available as part of the Xmipp software package inside of the Scipion framework, and also through the command-line in the standalone version of Xmipp. |
| مصطلحات الفهرس: | artículo |
| URL: | Journal of structural biology Publisher's version Sí info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104757RB-I00/ES/AIM-CRYOEM: PROCESAMIENTO DE IMAGEN AVANZADO ORIENTADO AL ANALISIS DE PARTICULAS INDIVIDUALES EN MICROSCOPIA ELECTRONICA EN CONDICIONES CRIOGENICAS |
| الاتاحة: | Open access content. Open access content openAccess |
| ملاحظة: | English |
| Other Numbers: | CTK oai:digital.csic.es:10261/358505 Journal of Structural Biology 10478477 10.1016/j.jsb.2023.108056 38101554 2-s2.0-85180588375 1442726746 |
| المصدر المساهم: | CSIC From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1442726746 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |