Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Survey of the Detection and Classification of Pulmonary Lesions via CT and X-Ray (2012.15442v1)

Published 31 Dec 2020 in eess.IV and cs.CV

Abstract: In recent years, the prevalence of several pulmonary diseases, especially the coronavirus disease 2019 (COVID-19) pandemic, has attracted worldwide attention. These diseases can be effectively diagnosed and treated with the help of lung imaging. With the development of deep learning technology and the emergence of many public medical image datasets, the diagnosis of lung diseases via medical imaging has been further improved. This article reviews pulmonary CT and X-ray image detection and classification in the last decade. It also provides an overview of the detection of lung nodules, pneumonia, and other common lung lesions based on the imaging characteristics of various lesions. Furthermore, this review introduces 26 commonly used public medical image datasets, summarizes the latest technology, and discusses current challenges and future research directions.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Yixuan Sun (25 papers)
  2. Chengyao Li (8 papers)
  3. Qian Zhang (309 papers)
  4. Aimin Zhou (43 papers)
  5. Guixu Zhang (19 papers)
Citations (2)

Summary

We haven't generated a summary for this paper yet.