Ultra‐compact tunable fiber laser for coherent anti‐Stokes Raman imaging

Gottschall, Thomas; Meyer‐Zedler, Tobias; Schmitt, Michael; Huber, Robert; Popp, Juergen; Tünnermann, Andreas; Limpert, Jens

doi:10.1002/jrs.6171

Cited by 7 publications

(4 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, our method can be implemented with a dual-fixed-wavelength picosecond pulse laser. Compact fiber lasers have been developed for CRS microscopy, [36][37][38] making it promising to perform our method with an integrated, miniaturized, and portable imaging device.…”

Section: Discussionmentioning

confidence: 99%

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Fang,

Wu,

Chen

et al. 2024

Advanced Intelligent Systems

View full text Add to dashboard Cite

Clinical guidelines for gastric cancer treatment recommend intraoperative peritoneal lavage cytology to detect free cancer cells. Patients with positive cytology require neoadjuvant chemotherapy instead of instant resection, and conversion to negative cytology results in improved survival. However, pathologists’ or artificial intelligence's accuracy of cytological diagnosis is disturbed by manually produced, unstandardized slides. In addition, the elaborate infrastructure makes cytology accessible to a limited number of medical institutes. This work develops CellGAN, a deep learning method that enables label‐free virtual peritoneal lavage cytology by producing virtual hematoxylin–eosin‐stained images with single‐color stimulated Raman scattering microscopy. A structural similarity loss is introduced to overcome the challenge of unsupervised virtual pathology techniques that cannot accurately present cellular structures. This method achieves a structural similarity of 0.820 ± 0.041 and a nucleus area consistency of 0.698 ± 0.102, indicating the staining fidelity outperforms the state‐of‐the‐art method. Diagnosis using virtually stained cells reaches 93.8% accuracy and substantial consistency with conventional staining. Single‐cell detection and classification on virtual slides achieve a mean average precision of 0.924 and an area under the receiver operating characteristic curve of 0.906, respectively. Collectively, this method achieves standardized and accurate virtual peritoneal lavage cytology and holds great potential for clinical translation.

show abstract

Section: Discussionmentioning

confidence: 99%

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Fang,

Wu,

Chen

et al. 2024

Advanced Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…Therefore, our method can be implemented with a device that is as simple as a dual-fixed-wavelength picosecond pulse laser. Currently, compact fiber lasers have been developed for CRS microscopy [36][37][38] , making it promising to perform our method with an integrated, miniaturized, and portable imaging device.…”

Section: Discussionmentioning

confidence: 99%

Label-free virtual peritoneal lavage cytology via deep-learning-assisted single-color stimulated Raman scattering microscopy

Fang,

Wu,

Chen

et al. 2024

Preprint

View full text Add to dashboard Cite

Clinical guidelines for gastric cancer treatment recommend intraoperative peritoneal lavage cytology to detect free cancer cells. Patients with positive cytology require neoadjuvant chemotherapy instead of instant resection and conversion to negative cytology results in improved survival. However, the accuracy of cytological diagnosis by pathologists or artificial intelligence is disturbed by manually-produced, unstandardized slides. In addition, the elaborate infrastructure makes cytology accessible to a limited number of medical institutes. Here, we developed CellGAN, a deep learning method that enables label-free virtual peritoneal lavage cytology by producing virtual hematoxylin-eosin-stained images with single-color stimulated Raman scattering microscopy. A structural similarity loss was introduced to overcome the challenge of existing unsupervised virtual pathology techniques unable to present cellular structures accurately. This method achieved a structural similarity of 0.820±0.041 and a nucleus area consistency of 0.698±0.102, indicating the staining fidelity outperforming the state-of-the-art method. Diagnosis using virtually stained cells reached 93.8% accuracy and substantial consistency with conventional staining. Single-cell detection and classification on virtual slides achieved a mean average precision of 0.924 and an area under the receiver operating characteristic curve of 0.906, respectively. Collectively, this method achieves standardized and accurate virtual peritoneal lavage cytology and holds great potential for clinical translation.

show abstract

“…Individual elements of the FWM setup are partially inspired by [4]- [6] (Figure 1). The pump source of the FWM process is a home-built 1064 nm MOPA fiber laser (Figure 1, green), which can output up to 100 kW peak power at 100 ps pulses and a repetition rate of 500 kHz.…”

Section: Methodsmentioning

confidence: 99%

900 nm swept source FDML laser with kW peak power

Lamminger¹,

Hakert²,

Lotz³

et al. 2023

Fiber Lasers XX: Technology and Systems

View full text Add to dashboard Cite

A wavelength agile 900 nm 2.5 kW peak power fiber laser is created by four-wave mixing (FWM) in a photonic crystal fiber (PCF), while amplifying a 1300 nm Fourier-domain mode-locked (FDML) laser. The FWM process is pumped by a home-built 1064 nm master oscillator power amplifier (MOPA) laser and seeded by a home-built 1300 nm FDML laser, generating high power pulses at wavelengths, where amplification by active fiber media is difficult. The 900 nm pulses have a spectral linewidth of 70 pm, are tunable over 54 nm and have electronic pulse-to-pulse tuning capability. These pulses can be used for nonlinear imaging like two-photon or coherent anti-Stokes Raman microscopy (CARS) microscopy including spectro-temporal laser imaging by diffracted excitation (SLIDE) and time-encoded (Tico) stimulated Raman microscopy.

show abstract

Ultra‐compact tunable fiber laser for coherent anti‐Stokes Raman imaging

Cited by 7 publications

References 47 publications

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Label-free virtual peritoneal lavage cytology via deep-learning-assisted single-color stimulated Raman scattering microscopy

900 nm swept source FDML laser with kW peak power

Contact Info

Product

Resources

About