Taking advantage of hyperspectral imaging classification of urinary stones against conventional infrared spectroscopy

Abstract

The analysis of urinary stones is mandatory for the best management of the disease after the stone passage in order to prevent further stone episodes. Thus the use of an appropriate methodology for an individualized stone analysis becomes a key factor for giving the patient the most suitable treatment. A recently developed hyperspectral imaging methodology, based on pixel-to-pixel analysis of near-infrared spectral images, is compared to the reference technique in stone analysis, infrared (IR) spectroscopy. The developed classification model yields >90% correct classification rate when compared to IR and is able to precisely locate stone components within the structure of the stone with a 15 µm resolution. Due to the little sample pretreatment, low analysis time, good performance of the model, and the automation of the measurements, they become analyst independent; this methodology can be considered to become a routine analysis for clinical laboratories.

Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

“…Preliminary research demonstrates that HSI has potential for providing diagnostic information for a myriad of diseases, including anemia, hypoxia, cancer detection, skin lesion and ulcer identification, urinary stone analysis, enhanced endoscopy, and many potential others in development. [11][12][13][14][15][16][17][18][19][20][21][22] Supervised machine learning and artificial intelligence algorithms have demonstrated the ability to classify images after being allowed to learn features from training or example images. One such method, convolutional neural networks (CNNs), has demonstrated astounding performance at image classification tasks due to their capacity for robust handling of training sample variance and ability to extract features from large training data sizes.…”

Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains

“…In comparison, most other approaches are more costly and time-consuming [ 109 ]. HSI has already been proven to offer valuable diagnostic information for identifying the grades of anaemia and hypoxia, detecting cancer, distinguishing between amalgam tattoos and other dark-pigmented intraoral lesions, and analyzing urinary stones [ [110] , [111] , [112] , [113] , [114] , [115] , [116] , [117] , [118] , [119] , [120] , [121] , [122] , [123] , [124] ]. Thus, HSI already provides data for endoscopy [ 125 , 126 ], dermatology [ 127 ], macroscopic investigations [ [128] , [129] , [130] ], histology [ 116 , 117 , [131] , [132] , [133] ] and organ viability assessment in the course of ex-situ machine perfusion [ 107 ].…”

New perspectives of hyperspectral imaging for clinical research

“…92–94 So far, HSI provides diagnostic information for anemia, hypoxia, cancer detection, skin lesions and ulcer identification, and urinary stone analysis. 12–14,95–106 Additional applications range from in vivo to ex vivo measurements including image-guided surgery, 12,106–108 endoscopy, 78,109 dermatology, 110 macroscopic investigations of ex-vivo tissue specimens 111–113 and histology. 13,14,114…”