Musical Neurofeedback Advancements, Feedback Modalities, and Applications: A Systematic Review.

The field of EEG-Neurofeedback (EEG-NF) training has showcased significant promise in treating various mental disorders, while also emerging as a cognitive enhancer across diverse applications. The core principle of EEG-NF involves consciously guiding the brain in desired directions, necessitating active engagement in neurofeedback (NF) tasks over an extended period. Music listening tasks have proven to be effective stimuli for such training, influencing emotions, mood, and brainwave patterns.

Computer-aided automated diminutive colonic polyp detection in colonoscopy by using deep machine learning system; first indigenous algorithm developed in India.

Background: Colonic polyps can be detected and resected during a colonoscopy before cancer development. However, about 1/4th of the polyps could be missed due to their small size, location or human errors. An artificial intelligence (AI) system can improve polyp detection and reduce colorectal cancer incidence.

Feasibility of Quantitative Tissue Characterization Using Novel Parameters Extracted From Photoacoustic Power Spectrum Considering Multiple Absorbers.

Frequency domain analysis of radio frequency signal is performed to differentiate between different tissue categories in terms of spectral parameters. However, due to complex relationship between the absorber size and spectral parameters, they cannot be used for quantitative tissue characterization. In an earlier study, we showed that using linear relationship between absorber size and two new spectral parameters namely number of lobes and average lobe width, absorber size can be successfully recovered from photoacoustic signal generated by single absorber.

Computation of Photoacoustic Absorber Size from Deconvolved Photoacoustic Signal Using Estimated System Impulse Response.

Photoacoustic signal recorded by photoacoustic imaging system can be modeled as convolution of initial photoacoustic response by the photoacoustic absorber with the system impulse response. Our goal was to compute the size of photoacoustic absorber using the initial photoacoustic response, deconvolved from the recorded photoacoustic data. For deconvolution, we proposed to use the impulse response of the photoacoustic system, estimated using discrete wavelet transform based homomorphic filtering.

Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids.

Objectives: This study investigated the capability of spectral parameters, extracted by frequency domain analysis of photoacoustic signals, to differentiate among malignant, benign, and normal thyroid tissue.

Methods: We acquired multiwavelength photoacoustic images of freshly excised thyroid specimens collected from 50 patients who underwent thyroidectomy after having a diagnosis of suspected thyroid lesions. A thyroid cytopathologist marked histologic slides of each tissue specimen.

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates: Ex Vivo Study With Human Prostates.

Objectives: The purpose of this study was to investigate the feasibility of differentiating malignant prostate from benign prostatic hyperplasia (BPH) and normal prostate tissue by performing frequency domain analysis of photoacoustic images acquired at 2 different wavelengths.

Methods: We performed multiwavelength photoacoustic imaging on freshly excised human prostate specimens taken from a total of 30 patients undergoing prostatectomy for biopsy-confirmed prostate cancer. Histologic slides marked by a genitourinary pathologist were used as ground truth to define regions of interest (ROIs) in the photoacoustic images.