At VISION 2026, Raytron OEM showcased its cutting-edge infrared imaging technologies, offering solutions to enhance industrial automation and machine vision systems.

Background: Early detection and monitoring of wound-related complications after total knee arthroplasty (TKA) are critical to optimize outcomes and preserve implants. Conventional postoperative monitoring relies on in-person assessment and patient-reported symptoms, which may delay recognition. Noncontact imaging acquired in the clinic or at home offers a potential route to earlier and more consistent assessment. Objective: This study aimed to evaluate the technical #feasibility and performance of a multimodal AI system integrating electro-optical (EO) and infrared imaging for postoperative wound assessment following TKA and to explore clinical factors associated with early complications. Methods: We conducted a single-center prospective cohort study of 749 patients undergoing primary TKA. Patients underwent standardized multimodal data collection at scheduled postoperative visits. EO-based models localized surgical landmarks and segmented complication-oriented tissue states; a fine-tuned vision-language model provided protocol verification and contextual visual reasoning. EO landmarks mapped to thermal space via deterministic alignment, followed by infrared region-of-interest segmentation and thermal classification. Each module was evaluated on a defined held-out set. The thermal classifier was assessed out-of-fold under 5-fold cross-validation with folds grouped by patient, in knees imaged on postoperative day 14 or later. Discrimination for clinician-adjudicated infection-related complications served as the primary outcome. Comorbidities and baseline laboratory values were explored for associations with complications. Results: Among 749 patients, 26 (3.5%) had a clinician-adjudicated infection-related complication. On held-out evaluation, the EO landmark detector reached a sensitivity of 0.967 (95% CI 0.954-0.979) and positive predictive value of 0.955 (95% CI 0.940-0.970), and the wound-tissue segmentation model reached a sensitivity of 0.845 (95% CI 0.833-0.857) and positive predictive value of 0.759 (95% CI 0.744-0.772). Infrared region-of-interest extraction isolated the surgical field with a mean intersection-over-union of 0.985 (SD 0.008; 95% CI 0.984-0.986) across 178 held-out patients. The trained thermal classifier discriminated infected scans with an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI 0.959-0.992) in out-of-fold, patient-grouped cross-validation. At a representative operating point, sensitivity was 0.808 (95% CI 0.65-0.92), specificity 0.974 (95% CI 0.96-0.99), positive predictive value 0.618 (95% CI 0.49-0.78), and negative predictive value 0.990 (95% CI 0.98-1.00). Exploratory analyses showed nominal associations of chronic kidney disease and diabetes mellitus with postoperative complications that did not remain significant after multiplicity correction. Conclusions: In this formative study, a multimodal EO and infrared imaging pipeline demonstrated technical #feasibility for postoperative wound assessment following TKA, providing noncontact discrimination of infection-related complications that compared favorably with established adjuncts. This work provides proof-of-concept for multimodal imaging-based assessment and defines the technical requirements for the prospective, multicenter external validation needed to establish clinical utility.

Background: Scores and prediction models, such as the MESS score for trauma and the Wifi classification for diabetic foot ulcers, help in the decision-making process of amputation. However, they can be subjective as they depend on the experience of the medical staff applying them. Objective: Assess the impact of temperature measurement using infrared thermal imaging in extremities salvage. Methods: We included 29 patients who sought a second opinion after an amputation recommendation. Infrared thermographic images were acquired to measure the temperature differences (ΔT) between the injured and uninjured limbs. For the salvaged limbs, we provided clinical follow-up until 12 weeks. Results: Of the patients enrolled in the study, 27 limbs were salvaged. Thermographic images allowed the discrimination of two groups: the first group of 18 patients with negative deltas, ΔT -3.6°C ± 1.99, and a second group of 9 patients with positive deltas, ΔT of 3.36°C ±2.71. None of the groups had progression to enlargement of their delta in the first 5 days, and at the twelfth week, ΔT approached 0°C at wound closure. For the two patients who required amputation, one patient showed an initial negative ΔT of -4.3°C, which worsened to -5°C by the fifth day, and the other patient showed an initial negative of -4.5°C, which worsened to -5.8°C by the fifth day. Conclusions: Digital infrared thermography is a tool that can help guide limb salvage in patients with uncertain clinical diagnoses. This imaging modality allows visualization of thermal differences and patterns derived from thermal changes in patients at risk of limb amputation.

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