Journal of biophotonics最新文献

Photoacoustic Microscopy Imaging and Region-Specific Segmentation of Ileocecal Malignant Tumor and Mixed Hemorrhoid Tissue Sections. 回盲部恶性肿瘤和混合痔组织切片的光声显微镜成像和区域特异性分割。

IF 2.3

Journal of biophotonics Pub Date : 2025-10-09 DOI: 10.1002/jbio.202500169

Xiaopeng Wang, Menghan Cai, Ruotong Mu, Chaoyong Liu, Yuyang Han, Zhennian Xie, Dongbing Li, Xiaojing An, Jingtao Li, Chaojun Niu, Qiang Yang, Qiang Liu

{"title":"Photoacoustic Microscopy Imaging and Region-Specific Segmentation of Ileocecal Malignant Tumor and Mixed Hemorrhoid Tissue Sections.","authors":"Xiaopeng Wang, Menghan Cai, Ruotong Mu, Chaoyong Liu, Yuyang Han, Zhennian Xie, Dongbing Li, Xiaojing An, Jingtao Li, Chaojun Niu, Qiang Yang, Qiang Liu","doi":"10.1002/jbio.202500169","DOIUrl":"https://doi.org/10.1002/jbio.202500169","url":null,"abstract":"The sensitivity of the photoacoustic effect to hemoglobin and structural features in biological tissues has led to its wide application in biomedical research, including vascular imaging and tumor tissue detection. In this study, we customed an optical-resolution photoacoustic microscopy system to analyze tissue sections derived from mixed hemorrhoids and ileocecal malignant tumors. Experimental results show that photoacoustic microscopy system accurately captures tissue morphology, revealing the edges and microvessel networks in mixed hemorrhoids and the irregular boundaries and mass-like structures in ileocecal tumors. Furthermore, this study employed a morphological approach to quantitatively analyze specific regional features in colorectal tissue images. Experimental results demonstrate that photoacoustic microscopy can accurately capture the boundaries in hemorrhoid regions, providing clinical guidance for assessing hemorrhoid types. It can also distinguish ileocecal tumor tissue from healthy ileocecal tissue based on tumor boundary characteristics, showing significant potential to improve both clinical diagnostic accuracy and surgical resection efficiency.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500169"},"PeriodicalIF":2.3,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Instant Minimally Invasive Detection of Lung Cancer Through Fiber Optical Generation and Detection of Plasmonic Nanobubbles Around TiN Nanoparticles. 通过光纤产生和检测TiN纳米粒子周围等离子体纳米气泡的肺癌即时微创检测。

IF 2.3

Journal of biophotonics Pub Date : 2025-10-03 DOI: 10.1002/jbio.202500326

Dmitri Lapotko, Ekaterina Lukianova

{"title":"Instant Minimally Invasive Detection of Lung Cancer Through Fiber Optical Generation and Detection of Plasmonic Nanobubbles Around TiN Nanoparticles.","authors":"Dmitri Lapotko, Ekaterina Lukianova","doi":"10.1002/jbio.202500326","DOIUrl":"https://doi.org/10.1002/jbio.202500326","url":null,"abstract":"Plasmonic nanobubbles (PNB) are on-demand transient vapor nanobubbles generated around laser pulse-heated plasmonic nanoparticles (NP). Despite promising in vivo tests, their clinical translation is delayed by complex lasers, bulky optical guides, and thermally fragile gold NPs with low PNB generation efficacy. In clinics, there is an unmet demand for in vivo real-time detection of microscopic cancers. Here, we resolve these limitations with an all-new combination of long and safe infrared laser pulses, small biocompatible titanium nitride (TiN) NPs for cancer targeting, and an optical fiber probe for minimally invasive PNB generation and detection in vivo. In water suspensions, tissue, and human lung cancer animal models, TiN NPs efficiently generated PNBs with 325 ps/1064 nm laser pulses. A PNB combination device instantly diagnosed lung cancer in animals with close to 100% sensitivity and specificity. The developed PNB combination device will support minimally invasive clinical applications for real-time high-sensitivity cancer diagnosis during biopsy and surgery.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500326"},"PeriodicalIF":2.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145226524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-Destructive and Real-Time Virtual Staining of Spermatozoa via Dark-Field Microscopy. 暗场显微镜下精子的无损实时虚拟染色。

IF 2.3

Journal of biophotonics Pub Date : 2025-10-01 DOI: 10.1002/jbio.202500339

Jiahao Wang, Xiaohua Liu, Lijun Wei, Shenghui Zhu, Siqi Zhu, Lu Han, Xinzhong Zhang

引用次数: 0

Multispectral Blood Cell Image Analysis via Deep Learning With YOLOv5. 基于YOLOv5的深度学习多光谱血细胞图像分析。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-28 DOI: 10.1002/jbio.202500384

Gang Li, Guiming Fu, Honghui Zeng, Kang Wang, Jerin Tasnim Humayra, Guizhong Liu, Ling Lin

{"title":"Multispectral Blood Cell Image Analysis via Deep Learning With YOLOv5.","authors":"Gang Li, Guiming Fu, Honghui Zeng, Kang Wang, Jerin Tasnim Humayra, Guizhong Liu, Ling Lin","doi":"10.1002/jbio.202500384","DOIUrl":"https://doi.org/10.1002/jbio.202500384","url":null,"abstract":"Blood cell counting is vital for medical diagnosis, and image recognition offers an automated approach. While most studies rely on microscopic images, these provide limited information. In contrast, multispectral imaging captures additional optical characteristics, improving the delineation of cellular boundaries and structures. This paper presents a blood cell recognition method based on multispectral imaging and YOLOv5. Blood cell images at five wavelengths were fused for multispectral information. The standard and modified YOLOv5 models were trained and tested on single-wavelength and multispectral images. Experimental results demonstrate that, compared with single-wavelength imaging, multispectral imaging markedly enhances the recognition performance of blood cells, yielding identification precision values of 99.9% for red blood cells and 96.1% for platelets. For white blood cells, which are relatively scarce, the recognition precision reached 98.9%, representing a 12.26% improvement over the best-performing single-wavelength model. Multispectral imaging shows significant potential for high-precision detection of rare cells.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500384"},"PeriodicalIF":2.3,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145188098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effects of Photobiomodulation Adjunct Therapy via Superpulsed 904 nm Laser in Patients With Second-Degree Burns: Randomized Controlled Clinical Trial. 超脉冲904nm激光光生物调节辅助治疗二度烧伤的效果：随机对照临床试验。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-24 DOI: 10.1002/jbio.202500386

Divya Yadav, Alpesh K Sharma, Komal Tripathi, Sujata Sarabahi, Amita Gupta, Suniti Kale, Asheesh Gupta

{"title":"Effects of Photobiomodulation Adjunct Therapy via Superpulsed 904 nm Laser in Patients With Second-Degree Burns: Randomized Controlled Clinical Trial.","authors":"Divya Yadav, Alpesh K Sharma, Komal Tripathi, Sujata Sarabahi, Amita Gupta, Suniti Kale, Asheesh Gupta","doi":"10.1002/jbio.202500386","DOIUrl":"https://doi.org/10.1002/jbio.202500386","url":null,"abstract":"Photobiomodulation therapy (PBMT) using near-infrared (NIR) light offers a non-invasive healing approach with deep-tissue penetration that enhances cellular proliferation, mitochondrial bioenergetics, reduces inflammation, and restores functions. However, clinical evidence for NIR-PBMT in burn care remains limited. This randomized, active-controlled trial evaluated the effects of 904 nm superpulsed laser NIR-PBMT as an adjunct to standard care (SOC; 1% silver-sulfadiazine, paraffin-gauze) for second-degree burn patients. Participants received either sham-exposed (n = 12) or 904 nm-PBMT (n = 12; 100 Hz frequency, 200-ns pulse width, 10 min, 1.1 J/session, twice weekly). The study evaluated re-epithelialization time, wound reduction, pain intensity (VAS score), blood PCT/CRP levels, and microbial load. NIR-PBMT significantly (p < 0.05) accelerated healing, re-epithelialization (8.3 vs. 12.6 days), wound reduction, granulation tissue formation, and decreased pain compared to sham-exposed. Neither group showed evidence of microbial infection or changes in PCT/CRP levels. These findings indicate that NIR-PBMT is an effective non-invasive adjunct therapy for faster repair of second-degree burns. Further, large-scale trials are needed.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500386"},"PeriodicalIF":2.3,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145139450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Accurate Diagnosis of Cutaneous Squamous Cell Carcinoma Based on Spatio-Spectral Fusion Features. 基于空间光谱融合特征的皮肤鳞状细胞癌准确诊断研究。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-22 DOI: 10.1002/jbio.202500146

Jiaqi Yong, Xiaojing Yu, Chongxuan Tian, Yanhai Zhang, Qi Zhao, Donghai Wang, Wei Li

{"title":"Research on Accurate Diagnosis of Cutaneous Squamous Cell Carcinoma Based on Spatio-Spectral Fusion Features.","authors":"Jiaqi Yong, Xiaojing Yu, Chongxuan Tian, Yanhai Zhang, Qi Zhao, Donghai Wang, Wei Li","doi":"10.1002/jbio.202500146","DOIUrl":"https://doi.org/10.1002/jbio.202500146","url":null,"abstract":"Cutaneous squamous cell carcinoma (SCC), a prevalent non-melanoma skin malignancy, poses significant diagnostic challenges due to the limitations of conventional clinical methods. This study introduces an advanced diagnostic framework leveraging hyperspectral imaging (HSI) to enhance SCC detection accuracy. The proposed methodology integrates Gray-Level Co-occurrence Matrix, Gabor filters, and Local Binary Patterns for spatial feature extraction, combined with Gramian Angular Field, Markov Transition Field, and Recurrence Plot for spatio-spectral feature transformation. A novel multi-scale hybrid transformer (MSHT) model is developed to classify skin lesions using microscopic HSI data, capturing both local texture details and global spectral-spatial dependencies through hybrid convolutional and self-attention mechanisms. Comparative experiments demonstrate the MSHT model's superior performance, achieving sensitivities of 0.88, 0.84, and 0.87 for actinic keratosis (AK), seborrheic keratosis (SK), and SCC, respectively. This research establishes a robust diagnostic paradigm for SCC and advances the clinical application of HSI technology through rigorous validation.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500146"},"PeriodicalIF":2.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on the Effect of Dual-Beam Laser Process Parameters on the Mechanical Properties and Thermal Damage of Skin Tissue Welding. 双光束激光工艺参数对皮肤组织焊接力学性能及热损伤影响的研究。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-18 DOI: 10.1002/jbio.202500364

Jun Huang, Mintao Yan, Yanyu Li, Yuxin Chen, Kehong Wang

引用次数: 0

Hyperspectral Imaging Combined With Machine Learning Methods to Quantify the Facial Skin Melanin and Erythema. 高光谱成像结合机器学习方法量化面部皮肤黑色素和红斑。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-18 DOI: 10.1002/jbio.202500303

Liangzhuang Wei, Xiangwei Yi, Wei Cheng, Yanyun Ma, Yandan Lin

{"title":"Hyperspectral Imaging Combined With Machine Learning Methods to Quantify the Facial Skin Melanin and Erythema.","authors":"Liangzhuang Wei, Xiangwei Yi, Wei Cheng, Yanyun Ma, Yandan Lin","doi":"10.1002/jbio.202500303","DOIUrl":"https://doi.org/10.1002/jbio.202500303","url":null,"abstract":"Melanin deposition and erythema mainly constitute physiological responses of the skin to environmental changes and represent important factors evaluating and diagnosing the skin conditions. This study investigates the critical roles of melanin and hemoglobin in skin-light interaction and combines spectral reflectance with single-point pigment values (collected by Mexameter MX18) to achieve the objective imaging skin color assessment. Feature wavelengths selected by the competitive adaptive reweighted sampling algorithm aligned well with narrow wavelength band designed by MX18, effectively removing redundant data while maintaining the model accuracy. Furthermore, seven machine learning methods were compared and evaluated, among which the stacked generalization model demonstrated the best performance (RMSEV = 14.23, <math> <semantics> <mrow><msubsup><mi>R</mi> <mi>v</mi> <mn>2</mn></msubsup> <mo>=</mo> <mn>0.8634</mn></mrow> <annotation>$$ {R}_v^2=0.8634 $$</annotation></semantics> </math> , RPDv = 2.706 for melanin index; RMSEV = 31.74, <math> <semantics> <mrow><msubsup><mi>R</mi> <mi>v</mi> <mn>2</mn></msubsup> <mo>=</mo> <mn>0.7505</mn></mrow> <annotation>$$ {R}_v^2=0.7505 $$</annotation></semantics> </math> , RPDv = 2.002 for erythema index). Finally, hyperspectral imaging technology enabled the visualization of skin pigment distribution, providing a rapid and non-invasive analytical tool for dermatological diagnosis and aesthetic evaluation.","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500303"},"PeriodicalIF":2.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145088732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-View Transport of Intensity Phase Imaging-Based Flow Cytometry for Label-Free Cell Analysis and Classification. 基于双视传输的强度相位成像流式细胞术用于无标记细胞分析和分类。

IF 2.3

Journal of biophotonics Pub Date : 2025-09-15 DOI: 10.1002/jbio.202500286

Wei Yu, Yaxi Li, Aihui Sun, Shouyu Wang

引用次数: 0

Non-Invasive Precise Classification of Glomerular Diseases in Urine Based on Hyperspectral Technology. 基于高光谱技术的尿肾小球疾病无创精确分类

IF 2.3

Journal of biophotonics Pub Date : 2025-09-15 DOI: 10.1002/jbio.202500208

Shenghan Qu, Chongxuan Tian, Guixi Zheng, Zhengshuai Jiang, Xiaming Gu, Jiaxin Lv, Donghai Wang, Wei Li

引用次数: 0