A Survey on Optical Coherence Tomography—Technology and Application

Bioengineering, Год журнала: 2025, Номер 12(1), С. 65 - 65

Опубликована: Янв. 14, 2025

This paper reviews the main research on Optical Coherence Tomography (OCT), focusing progress and advancements made by researchers over past three decades in its methods medical imaging applications. By analyzing existing studies developments, this review aims to provide a foundation for future field.

Язык: Английский

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Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 19, 2025

Abstract The most dangerous form of cancer is breast cancer. This disease life-threatening because its aggressive nature and high death rates. Therefore, early discovery increases the patient’s survival. Mammography has recently been recommended as diagnosis technique. Mammography, expensive exposure person to radioactivity. Thermography a less invasive affordable technique that becoming increasingly popular. Considering this, recent deep learning-based approach executed by thermography images. Initially, images are chosen from online sources. collected being preprocessed Contrast Limited Adaptive Histogram Equalization (CLAHE) contrasting enhancement methods improve quality brightness Then, optimal binary thresholding done segment images, where optimized value using developed Rock Hyraxes Dandelion Algorithm Optimization (RHDAO). A newly implemented learning structure StackVRDNet used for further processing diagnosing segmented fed framework, Visual Geometry Group (VGG16), Resnet, DenseNet employed constructing this model. relevant features extracted usingVGG16, DenseNet, then obtain stacked weighted feature pool features, weight optimization with help RHDAO. final classification performed StackVRDNet, results obtained at layer VGG16, DenseNet. higher scoring method rated ensuring results. Here, parameters present within via RHDAO simulation outcomes model achieve 97.05% 86.86% in terms accuracy precision, respectively. effectiveness designed methd analyzed conventional models various performance measures.

Язык: Английский

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Advancements in photoacoustic imaging for cancer diagnosis and treatment

International Journal of Pharmaceutics, Год журнала: 2024, Номер unknown, С. 124736 - 124736

Опубликована: Сен. 1, 2024

Язык: Английский

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AI‐Driven Microscopy: Cutting‐Edge Approach for Breast Tissue Prognosis Using Microscopic Images

Microscopy Research and Technique, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Microscopic imaging aids disease diagnosis by describing quantitative cell morphology and tissue size. However, the high spatial resolution of these images poses significant challenges for manual evaluation. This project proposes using computer-aided analysis methods to address challenges, enabling rapid precise clinical diagnosis, course analysis, prognostic prediction. research introduces advanced deep learning frameworks such as squeeze-and-excitation dilated dense convolution blocks tackle complexities quantifying small intricate breast cancer tissues meeting real-time requirements pathological image analysis. Our proposed framework integrates a convolutional network (DenseNet) with an attention mechanism, enhancing capability accurate assessments. These multi-classification models facilitate prediction segmentation lesions in microscopic leveraging lightweight multi-scale feature extraction, dynamic region attention, sub-region classification, regional regularization loss functions. will employ transfer paradigms data enhancement enhance models' further prevent overfitting. We propose fine-tuning employing pre-trained architectures VGGNet-19, ResNet152V2, EfficientNetV2-B1, DenseNet-121, modifying final pooling layer each model's last block SPP associated BN layer. The study uses labeled unlabeled robust features classification abilities. method reduces costs time traditional methods, alleviating burden labeling computational pathology. goal is provide sophisticated, efficient solution, improving outcomes advancing field. model, trained, validated, tested on microscope dataset, achieved recognition accuracy 99.6% benign malignant secondary 99.4% eight subtypes classification. approach demonstrates substantial improvement compared existing which generally report lower accuracies subtype ranging between 85% 94%. level underscores potential our reliable diagnostic support, precision decision-making.

Язык: Английский

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Identification of depressing tweets using natural language processing and machine learning: Application of grey relational grades

Journal of Radiation Research and Applied Sciences, Год журнала: 2025, Номер 18(1), С. 101299 - 101299

Опубликована: Янв. 20, 2025

Язык: Английский

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Co-linear Hexa-Mirror-Based Multi-Periodic Structured Illumination Microscopy

Nano Letters, Год журнала: 2025, Номер unknown

Опубликована: Янв. 29, 2025

Structured illumination microscopy (SIM) is a robust wide-field optical nanoscopy technique. Several approaches are implemented to improve SIM's resolution capability (∼2-fold). However, achieving high with large field of view (FOV) still challenging. We present tilt-mirror-based multi-periodic SIM for large-FOV super-resolution microscopy. The sample illuminated by structured pattern generated six-beam interference using custom-designed mirror mount. achieve 3.16-fold improvement while 20×/0.40 numerical-aperture objective that supports FOV (0.53 mm × 0.34 mm). This overcomes the high-space-bandwidth product challenge, 9.98-fold improvement. mMP-SIM decouples and collection paths, enabling scalable over FOV. By 28×/0.80 lens, an 170 nm 0.40 0.25 imaging area demonstrated. proof-of-principle experimental demonstration performed both fluorescent beads biosample like U2OS (human bone osteosarcoma) cells.

Язык: Английский

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Validation of the Barcelona Magnetic Resonance Imaging Predictive Model for Significant Prostate Cancer Detection in Men Undergoing Mapping per 0.5 Mm-Core Targeted Biopsies of Suspicious Lesions and Perilesional Areas

Cancers, Год журнала: 2025, Номер 17(3), С. 473 - 473

Опубликована: Янв. 31, 2025

Background/Objectives: Validation of predictive models (PMs) is crucial to be implemented in new populations or when advances diagnostic approaches occurred. The aim this study validate the BCN-MRI PM for sPCa a highly effective prostate biopsy protocol used. Methods: A prospective cohort 457 men suspected having PCa, whom MRI results were reported with Prostate Imaging-Reporting and Data System (PI-RADS) v 2.1, underwent per 0.5 mm-core mapping targeted suspicious lesions perilesional areas, followed by 12-core-systematic biopsy. These procedures took place between 1 February 2022, 29 2024, at reference center individual likelihood was assessed through risk calculator. Results: overall detection rate 58.3%. calibration curve showed an appropriate accuracy expected observed probabilities discrimination ability yielding area under (AUC) 0.862 (95% CI 0.828-0.896) comparable AUC 0.858 0.833-0.883) development cohort. application provided net benefit over performing biopsies on all men, avoiding 24.9% 95% sensitivity sPCa, compared 23.7% reduction Conclusions: We conclude that ready employed.

Язык: Английский

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Super-resolution segmentation of blurry pointer meter images based on frequency supervision

Measurement, Год журнала: 2025, Номер unknown, С. 117181 - 117181

Опубликована: Март 1, 2025

Язык: Английский

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Organotin(IV) complexes: Emerging Frontiers in anticancer therapeutics and bioimaging applications

Coordination Chemistry Reviews, Год журнала: 2025, Номер 534, С. 216582 - 216582

Опубликована: Март 13, 2025

Язык: Английский

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Dual-axis Generalized Cross Attention and Shape-aware Network for 2D medical image segmentation

Biomedical Signal Processing and Control, Год журнала: 2025, Номер 107, С. 107791 - 107791

Опубликована: Март 14, 2025

Язык: Английский

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