The authors report the characteristics of a diffraction-grating-free mid-wavelength infrared InP/In0.85Ga0.15As quantum well infrared photodetector focal plane array with a 640 × 512 format and a 15 m pitch. Combination of a normal incident radiation sensing ability of the high-x InxGa1-xAs quantum wells with a large gain property of the InP barriers led to a diffraction-grating-free quantum well infrared photodetector focal plane array with characteristics displaying great promise to keep the status of the quantum well infrared photodetector as a robust member of the new generation thermal imaging sensor family. The focal plane array exhibited excellent uniformity with noise equivalent temperature difference nonuniformity as low as 10% and a mean noise equivalent temperature difference below 20 mK with f/2 optics at 78 K in the absence of grating. Elimination of the diffraction-grating and large enough conversion efficiency (as high as 70% at a −3.5 V bias voltage) abolish the bottlenecks of the quantum well infrared photodetector technology for the new generation very small-pitch focal plane arrays.

Non-destructive testing (NDT) is generally used to estimate the compressive strength of concrete material without compromising its structural integrity. However, the available testing methods on the market have particular limitations that may restrict the accuracy of the results. Therefore, this study aimed to develop a new technique for measuring the compressive strength of geopolymer concrete using infrared imaging analysis and Thermal Diameter Variation (TDV) rate. The compressive strength range was designed within the target strength of 20, 30 and 40 MPa. The infrared image was captured on the preheated concrete surface using FLIR-ONE infrared camera. Based on the correlation between TDV rate and compressive strength, higher accuracy was obtained in the orange contour with an R2 of 0.925 than in the red contour with an R2 of 0.8867. It is apparent that infrared imaging analysis has excellent reliability to be used as an alternative NDT by focusing on the warmer region during the procedure.

Automated motion reduction in dynamic infrared imaging is on demand in clinical applications, since movement disarranges time−temperature series of each pixel, thus originating thermal artifacts that might bias the clinical decision. All previously proposed registration methods are feature based algorithms requiring manual intervention. The aim of this work is to optimize the registration strategy specifically for Breast Dynamic Infrared Imaging and to make it user−independent. We implemented and evaluated 3 different 3D time−series registration methods: 1. Linear affine, 2. Non−linear Bspline, 3. Demons applied to 12 datasets of healthy breast thermal images. The results are evaluated through normalized mutual information with average values of 0.70 ±0.03, 0.74 ±0.03 and 0.81 ±0.09 (out of 1) for Affine, Bspline and Demons registration, respectively, as well as breast boundary overlap and Jacobian determinant of the deformation field. The statistical analysis of the results showed that symmetric diffeomorphic Demons’ registration method outperforms also with the best breast alignment and non−negative Jacobian values which guarantee image similarity and anatomical consistency of the transformation, due to homologous forces enforcing the pixel geometric disparities to be shortened on all the frames. We propose Demons’ registration as an effective technique for time−series dynamic infrared registration, to stabilize the local temperature oscillation.

Whatever the type of surgery related to inner organs, traditional or robotic, the contact with them during surgery is a key moment for pursuing the intervention. Contacts by means of surgery instruments namely scalpels, staples, clamps, graspers, etc. are decisive moments. False, and erroneous touching and manoeuvring of organs operated on can cause irreversible damage as regard morphological aspects (outer impact) and physiological aspects (inner impact). The topic is a great challenge in the effort to measure and characterize damages. In general, electrical instruments for surgery employ the following technologies: ultrasound, radiofrequency (monopolar, and bipolar), and laser. They all result in thermal damages difficult to evaluate. The article proposes a method for a pre-screening of organ features during robotic surgery sessions by pointing out mechanical and thermal stresses. A dedicated modelling has been developed based on experimental activities during surgery session. The idea is to model tissue behaviour from real images to help surgeons to be aware of handling during surgery. This is the first step for generalization by considering the type of organ. The measurement acquisitions have been performed by means of an advanced external camera located over the surgery quadrant. The modelling and testing have been carried out on kidneys. The modelling, carried out through Comsol Multiphysics, is based on the bioheat approach. A further comparative technique has been implemented. It is based on computer vision for robotics. The findings of human tissue behavior exhibit reliable results.

This paper presents and assesses an inverse heat conduction problem (IHCP) solution procedure which was developed to determine the local convective heat transfer coefficient along the circumferential coordinate at the inner wall of a coiled pipe by applying the filtering technique approach to infrared temperature maps acquired on the outer tube’s wall. The data−processing procedure filters out the unwanted noise from the raw temperature data to enable the direct calculation of its Laplacian which is embedded in the formulation of the inverse heat conduction problem. The presented technique is experimentally verified using data that were acquired in the laminar flow regime that is frequently found in coiled−tube heat−exchanger applications. The estimated convective heat transfer coefficient distributions are substantially consistent with the available numerical results in the scientific literature.