Pulmonary Fissure Segmentation in CT Images Using Image Filtering and Machine Learning

The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation.

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Publication Details

Journal
Tomography
Published
2024-10-09
DOI
https://doi.org/10.3390/tomography10100121
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.40

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article

Pulmonary Fissure Segmentation in CT Images Using Image Filtering and Machine Learning

Anastasia Ananeva, Vladislav Ananev, В. А. Макаров, Mikhail Fufin et al.
1 citations
Tomography
Radiomics and Machine Learning in Medical Imaging
0.40
article

Pulmonary Fissure Segmentation in CT Images Using Image Filtering and Machine Learning

Anastasia Ananeva, Vladislav Ananev, В. А. Макаров, Mikhail Fufin, Vadim I. Alfimov
article en
1 citations

Abstract

The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation.

TomographyVol. 10(10)
Yaroslav-the-Wise Novgorod State University (RU)
Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 34%
Radiomics and Machine Learning in Medical Imaging
0.40
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