Calibration-Jitter: Augmentation of hyperspectral data for improved surgical scene segmentation.

Semantic surgical scene segmentation is crucial for accurately identifying and delineating different tissue types during surgery, enhancing outcomes and reducing complications. Hyperspectral imaging provides detailed information beyond visible color filters, offering an enhanced view of tissue characteristics. Combined with machine learning, it supports critical tumor resection decisions.

PoLambRimetry: a multispectral polarimetric atlas of lamb brain.

Significance: Mueller matrix imaging (MMI) is a comprehensive form of polarization imaging useful for assessing structural changes. However, there is limited literature on the polarimetric properties of brain specimens, especially with multispectral analysis.

Aim: We aim to employ multispectral MMI for an exhaustive polarimetric analysis of brain structures, providing a reference dataset for future studies and enhancing the understanding of brain anatomy for clinicians and researchers.

Computational Polarization Imaging In Vivo through Surgical Smoke Using Refined Polarization Difference.

In surgery, the surgical smoke generated during tissue dissection and hemostasis can degrade the image quality, affecting tissue visibility and interfering with the further image processing. Developing reliable and interpretable computational imaging methods for restoring smoke-affected surgical images is crucial, as typical image restoration methods relying on color-texture information are insufficient. Here a computational polarization imaging method through surgical smoke is demonstrated, including a refined polarization difference estimation based on the discrete electric field direction, and a corresponding prior-based estimation method, for better parameter estimation and image restoration performance.

Monoclonal Antibodies for Targeted Fluorescence-Guided Surgery: A Review of Applicability across Multiple Solid Tumors.

This study aims to review the status of the clinical use of monoclonal antibodies (mAbs) that have completed or are in ongoing clinical trials for targeted fluorescence-guided surgery (T-FGS) for the intraoperative identification of the tumor margins of extra-hematological solid tumors. For each of them, the targeted antigen, the mAb generic/commercial name and format, and clinical indications are presented, together with utility, doses, and the timing of administration. Based on the current scientific evidence in humans, the top three mAbs that could be prepared in a GMP-compliant bank ready to be delivered for surgical purposes are proposed to speed up the translation to the operating room and produce a few readily available "off-the-shelf" injectable fluorescent probes for safer and more effective solid tumor resection.

Fluorescence guided surgery imaging systems for breast cancer identification: a systematic review.

Significance: Breast-conserving surgery (BCS) is limited by high rates of positive margins and re-operative interventions. Fluorescence-guided surgery seeks to detect the entire lesion in real time, thus guiding the surgeons to remove all the tumor at the index procedure.

Aim: Our aim was to identify the optimal combination of a camera system and fluorophore for fluorescence-guided BCS.

A Comparison of Spectroscopy and Imaging Techniques Utilizing Spectrally Resolved Diffusely Reflected Light for Intraoperative Margin Assessment in Breast-Conserving Surgery: A Systematic Review and Meta-Analysis.

Up to 19% of patients require re-excision surgery due to positive margins in breast-conserving surgery (BCS). Intraoperative margin assessment tools (IMAs) that incorporate tissue optical measurements could help reduce re-excision rates. This review focuses on methods that use and assess spectrally resolved diffusely reflected light for breast cancer detection in the intraoperative setting.

A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery.

Purpose: A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time.

Surgical polarimetric endoscopy for the detection of laryngeal cancer.

The standard-of-care for the detection of laryngeal pathologies involves distinguishing suspicious lesions from surrounding healthy tissue via contrasts in colour and texture captured by white-light endoscopy. However, the technique is insufficiently sensitive and thus leads to unsatisfactory rates of false negatives. Here we show that laryngeal lesions can be better detected in real time by taking advantage of differences in the light-polarization properties of cancer and healthy tissues.

Introduction to the Biophotonics Congress 2022 feature issue.

A feature issue is being presented by a team of guest editors containing papers based on studies presented at the Optica Biophotonics Congress: Biomedical Optics held on April 24-27, 2022 in Fort Lauderdale, Florida, USA.

Self-supervised Monocular Depth Estimation with 3D Displacement Module for Laparoscopic Images.

We present a novel self-supervised training framework with 3D displacement (3DD) module for accurately estimating per-pixel depth maps from single laparoscopic images. Recently, several self-supervised learning based monocular depth estimation models have achieved good results on the KITTI dataset, under the hypothesis that the camera is dynamic and the objects are stationary, however this hypothesis is often reversed in the surgical setting (laparoscope is stationary, the surgical instruments and tissues are dynamic). Therefore, a 3DD module is proposed to establish the relation between frames instead of ego-motion estimation.

Simultaneous Depth Estimation and Surgical Tool Segmentation in Laparoscopic Images.

Surgical instrument segmentation and depth estimation are crucial steps to improve autonomy in robotic surgery. Most recent works treat these problems separately, making the deployment challenging. In this paper, we propose a unified framework for depth estimation and surgical tool segmentation in laparoscopic images.

Real-time Tracking and Classification of Tumor and Nontumor Tissue in Upper Gastrointestinal Cancers Using Diffuse Reflectance Spectroscopy for Resection Margin Assessment.

Importance: Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumor margins is of particular importance for curative cancer resection and improvement in overall survival. Current mapping techniques preclude a full resection margin assessment in real time.

Indocyanine green fluorescence image processing techniques for breast cancer macroscopic demarcation.

Re-operation due to disease being inadvertently close to the resection margin is a major challenge in breast conserving surgery (BCS). Indocyanine green (ICG) fluorescence imaging could be used to visualize the tumor boundaries and help surgeons resect disease more efficiently. In this work, ICG fluorescence and color images were acquired with a custom-built camera system from 40 patients treated with BCS.

Polarization-based smoke removal method for surgical images.

Smoke generated during surgery affects tissue visibility and degrades image quality, affecting surgical decisions and limiting further image processing and analysis. Polarization is a fundamental property of light and polarization-resolved imaging has been studied and applied to general visibility restoration scenarios such as for smog or mist removal or in underwater environments. However, there is no related research or application for surgical smoke removal.

Real-time tracking of a diffuse reflectance spectroscopy probe used to aid histological validation of margin assessment in upper gastrointestinal cancer resection surgery.

Significance: Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements.

Aim: This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue.

A systematic review of robotic surgery: From supervised paradigms to fully autonomous robotic approaches.

Background: From traditional open surgery to laparoscopic surgery and robot-assisted surgery, advances in robotics, machine learning, and imaging are pushing the surgical approach to-wards better clinical outcomes. Pre-clinical and clinical evidence suggests that automation may standardise techniques, increase efficiency, and reduce clinical complications.

Methods: A PRISMA-guided search was conducted across PubMed and OVID.

The Impact of Temporal Variation in Indocyanine Green Administration on Tumor Identification During Fluorescence Guided Breast Surgery.

Background: On average, 21% of women in the USA treated with Breast Conserving Surgery (BCS) undergo a second operation because of close positive margins. Tumor identification with fluorescence imaging could improve positive margin rates through demarcating location, size, and invasiveness of tumors. We investigated the technique's diagnostic accuracy in detecting tumors during BCS using intravenous indocyanine green (ICG) and a custom-built fluorescence camera system.

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. METHODS : An established modified Delphi approach for research priority setting was used.

Meta-analysis Comparing Fluorescence Imaging with Radioisotope and Blue Dye-Guided Sentinel Node Identification for Breast Cancer Surgery.

Introduction: Conventional methods for axillary sentinel lymph node biopsy (SLNB) are fraught with complications such as allergic reactions, skin tattooing, radiation, and limitations on infrastructure. A novel technique has been developed for lymphatic mapping utilizing fluorescence imaging. This meta-analysis aims to compare the gold standard blue dye and radioisotope (BD-RI) technique with fluorescence-guided SLNB using indocyanine green (ICG).