Study on lung CT image segmentation algorithm based on threshold-gradient combination and improved convex hull method.

Lung images often have the characteristics of strong noise, uneven grayscale distribution, and complex pathological structures, which makes lung image segmentation a challenging task. To solve this problems, this paper proposes an initial lung mask extraction algorithm that combines threshold and gradient. The gradient used in the algorithm is obtained by the time series feature extraction method based on differential memory (TFDM), which is obtained by the grayscale threshold and image grayscale features.

Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model.

Soybean plays an important role in food, medicine, and industry. The quality inspection of soybean is essential for soybean yield and the agricultural economy. However, soybean pest is an important factor that seriously affects soybean yield, among which leguminivora glycinivorella matsumura is the most frequent pest.

[Advance in nondestructive detection of fruit internal quality based on hyperspectral imaging].

The present paper reviews the development in the field of hyperspectral imaging technology for nondestructive detection of fruit internal quality in recent years up to the year 2007. With the increasing maturity of hyperspectral imaging technology, decline of cost for its hardware and software, and improvement in hyperspectral image data processing algorithms, hyperspectral imaging technology for fruit quality nondestructive detection has become a hot research topic. In order to track the latest research developments at home and abroad, the fruit internal quality (maturity, firmness, soluble solid content, water content) detection with hyperspectral imaging was reviewed, which would provide reference for Chinese researchers.