Potential for Photoacoustic Imaging of Neonatal Brain

Photoacoustic imaging is a hybrid imaging technique that combines many of the merits of both optical and ultrasound imaging. Photoacoustic imaging (PAI) has been hypothesized as a technique for imaging neonatal brain. However, PAI of the brain is more challenging than traditional methods (e.g. near infrared spectroscopy) due to the presence of the skull layer. To evaluate the potential limits the skull places on 3D PAI of the neonatal brain, we constructed a neonatal skull phantom (~1.52-mm thick) with a mixture of epoxy and titanium dioxide powder that provided acoustic insertion loss (1-5MHz) similar to human infant skull bone. The phantom was molded into a realistic infant skull shape by means of a CNC-machined mold that was based upon a 3D CAD model. Then, propagation of photoacoustic (PA) signals through the skull phantom was examined. A photoacoustic point source was raster-scanned within the imaging cavity of a 128-channel PAI system to capture the imaging operator with and without the intervening skull phantom layer. Then, effects of the skull phantom on PA signals and consequently on PA images was evaluated in detail. We captured 3D photoacoustic images of tubes filled with indocyanine green (ICG). The system was capable of reconstructing an image of a tube filled with 50 μM ICG in presence of the skull. Image processing method was developed to correct photoacoustic images from the effects of the skull. The method was tested on an image of an object captured through the skull, which demonstrated that the effects of the skull on PA images are predictable and modifiable

Medical Imaging Applications of Federated Learning

Since its introduction in 2016, researchers have applied the idea of Federated Learning (FL) to several domains ranging from edge computing to banking. The technique\u27s inherent security benefits, privacy-preserving capabilities, ease of scalability, and ability to transcend data biases have motivated researchers to use this tool on healthcare datasets. While several reviews exist detailing FL and its applications, this review focuses solely on the different applications of FL to medical imaging datasets, grouping applications by diseases, modality, and/or part of the body. This Systematic Literature review was conducted by querying and consolidating results from ArXiv, IEEE Xplorer, and PubMed. Furthermore, we provide a detailed description of FL architecture, models, descriptions of the performance achieved by FL models, and how results compare with traditional Machine Learning (ML) models. Additionally, we discuss the security benefits, highlighting two primary forms of privacy-preserving techniques, including homomorphic encryption and differential privacy. Finally, we provide some background information and context regarding where the contributions lie. The background information is organized into the following categories: architecture/setup type, data-related topics, security, and learning types. While progress has been made within the field of FL and medical imaging, much room for improvement and understanding remains, with an emphasis on security and data issues remaining the primary concerns for researchers. Therefore, improvements are constantly pushing the field forward. Finally, we highlighted the challenges in deploying FL in medical imaging applications and provided recommendations for future directions

Potential for photoacoustic imaging of the neonatal brain

Photoacoustic imaging (PAI) has been proposed as a non-invasive technique for imaging neonatal brain injury. Since PAI combines many of the merits of both optical and ultrasound imaging, images with high contrast, high resolution, and a greater penetration depth can be obtained when compared to more traditional optical methods. However, due to the strong attenuation and reflection of photoacoustic pressure waves at the skull bone, PAI of the brain is much more challenging than traditional methods (e.g. near infrared spectroscopy) for optical interrogation of the neonatal brain. To evaluate the potential limits the skull places on 3D PAI of the neonatal brain, we constructed a neonatal skull phantom (1.4-mm thick) with a mixture of epoxy and titanium dioxide powder that provided acoustic insertion loss (1-5MHz) similar to human infant skull bone. The phantom was molded into a realistic infant skull shape by means of a CNCmachined mold that was based upon a 3D CAD model. To evaluate the effect of the skull bone on PAI, a photoacoustic point source was raster scanned within the phantom brain cavity to capture the imaging operator of the 3D PAI system (128 ultrasound transducers in a hemispherical arrangement) with and without the intervening skull phantom. The resultant imaging operators were compared to determine the effect of the skull layer on the PA signals in terms of amplitude loss and time delay. © 2013 Copyright SPIE

Development of a Novel Truncated-correlation Photothermal Coherence Tomography for Non-invasive Biothermophotonic and Non-destructive Materials Imaging

Truncated-Correlation Photothermal Coherence Tomography (TC-PCT) is the most successful class of diffusion-wave methodologies to-date providing 3-D subsurface visualization. To extend depth range and axial and lateral resolution, a novel imaging system with improved instrumentation, and an optimized reconstruction algorithm over the conventional TC-PCT technique is developed in this PhD project. The enhanced TC-PCT system was then used for biomedical and non-destructive testing applications. First, we reported visualization of subsurface defects in a steel sample. The results demonstrate defect detection at the depth range of ∼4 mm in a steel sample, which exhibits dynamic range improvement by a factor of 2.6 compared to the conventional TC-PCT, the Lock-in Thermography and Thermal Wave radar. Lateral resolution in the steel sample was measured to be ∼ 31 μm. Second, we used the system to investigate the possibility of non-destructive imaging of an art object to identify features that often are invisible areas of vulnerability and damage. The enhanced TC-PCT modality identified all the defects such as empty holes, a hole filled with stucco, delaminations and natural features such as a wood knot and wood grain in different layers of the sample. The system was then used for biomedical applications, three of which are early demineralization in tooth sample, early detection of tumor in mice, and structural imaging of mouse brain. First, we introduced dental enhanced TC-PCT imaging with a current subsurface depth profilometric capability of ~ 3.8 mm. Second, the enhanced TC-PCT modality was presented for early in-vivo tumor detection and tested in imaging nude mice thighs. Precise measurement of the size and shape of the detected tumor was validated following histological analysis. Third, enhanced TC-PCT was developed for brain imaging and was successfully exhibited structures of the brain such as brain lobes, blood vessel, olfactory bulbs, and cerebellum.Ph.D.2021-07-21 00:00:0

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

The present review aims to analyze the application of infrared thermal imaging, aided by bio-heat models, as a tool for the diagnosis of skin and breast cancers. The state of the art of the related technical procedures, bio-heat transfer modeling, and thermogram post-processing methods is comprehensively reviewed. Once the thermal signatures of different malignant diseases are described, the updated thermographic techniques (steady-state and dynamic) used for cancer diagnosis are discussed in detail, along with the recommended best practices to ensure the most significant thermal contrast observable between the cancerous and healthy tissues. Regarding the dynamic techniques, particular emphasis is placed on innovative methods, such as lock-in thermography, thermal wave imaging, and rotational breast thermography. Forward and inverse modeling techniques for the bio-heat transfer in skin and breast tissues, supporting the thermographic examination and providing accurate data for training artificial intelligence (AI) algorithms, are reported with a special focus on real breast geometry-based 3D models. In terms of inverse techniques, different data processing algorithms to retrieve thermophysical parameters and growth features of tumor lesions are mentioned. Post-processing of infrared images is also described, citing both conventional processing procedures and applications of AI algorithms for tumor detection

Detection of Bacteria-Induced Early-Stage Dental Caries Using Three-Dimensional Mid-Infrared Thermophotonic Imaging

Tooth decay, or dental caries, is a widespread and costly disease that is reversible when detected early in its formation. Current dental caries diagnostic methods including X-ray imaging and intraoral examination lack the sensitivity and specificity required to routinely detect caries early in its formation. Thermophotonic imaging presents itself as a highly sensitive and non-ionizing solution, making it suitable for the frequent monitoring of caries progression. Here, we utilized a treatment protocol to produce bacteria-induced caries lesions. The lesions were imaged using two related three-dimensional photothermal imaging modalities: truncated correlation photothermal coherence tomography (TC-PCT) and its enhanced modification eTC-PCT. In addition, micro-computed tomography (μ-CT) and visual inspection by a clinical dentist were used to validate and quantify the severities of the lesions. The observational findings demonstrate the high sensitivity and depth profiling capabilities of the thermophotonic modalities, showcasing their potential use as a non-ionizing clinical tool for the early detection of dental caries