R-3 Repository :: Browsing by Author "Tang, Yubo"

Browsing by Author "Tang, Yubo"

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Deep learning extended depth-of-field microscope for fast and slide-free histology
(PNAS, 2020) Jin, Lingbo; Tang, Yubo; Wu, Yicheng; Coole, Jackson B.; Tan, Melody T.; Zhao, Xuan; Badaoui, Hawraa; Robinson, Jacob T.; Williams, Michelle D.; Gillenwater, Ann M.; Richards-Kortum, Rebecca R.; Veeraraghavan, Ashok; Bioengineering; Electrical and Computer Engineering
Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells—a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.
DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology
(Springer Nature, 2024) Jin, Lingbo; Tang, Yubo; Coole, Jackson B.; Tan, Melody T.; Zhao, Xuan; Badaoui, Hawraa; Robinson, Jacob T.; Williams, Michelle D.; Vigneswaran, Nadarajah; Gillenwater, Ann M.; Richards-Kortum, Rebecca R.; Veeraraghavan, Ashok; Bioengineering; Electrical and Computer Engineering
Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings.
Design and Evaluation of ScanCap: A Low-Cost, Reusable Tethered Capsule Endoscope with Blue-Green Illumination Imaging for Unsedated Screening and Early Detection of Barrett’s Esophagus
(MDPI, 2024) Hicheri, Cheima; Azimuddin, Ahad M.; Kortum, Alex; Bailey, Joseph; Tang, Yubo; Schwarz, Richard A.; Rosen, Daniel; Jain, Shilpa; Mansour, Nabil M.; Groth, Shawn; Vasavada, Shaleen; Rao, Ashwin; Maliga, Adrianna; Gallego, Leslie; Carns, Jennifer; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca; Bioengineering; Rice 360 Institute for Global Health
Esophageal carcinoma is the sixth-leading cause of cancer death worldwide. A precursor to esophageal adenocarcinoma (EAC) is Barrett’s Esophagus (BE). Early-stage diagnosis and treatment of esophageal neoplasia (Barrett’s with high-grade dysplasia/intramucosal cancer) increase the five-year survival rate from 10% to 98%. BE is a global challenge; however, current endoscopes for early BE detection are costly and require extensive infrastructure for patient examination and sedation. We describe the design and evaluation of the first prototype of ScanCap, a high-resolution optical endoscopy system with a reusable, low-cost tethered capsule, designed to provide high-definition, blue-green illumination imaging for the early detection of BE in unsedated patients. The tethered capsule (12.8 mm diameter, 35.5 mm length) contains a color camera and rotating mirror and is designed to be swallowed; images are collected as the capsule is retracted manually via the tether. The tether provides electrical power and illumination at wavelengths of 415 nm and 565 nm and transmits data from the camera to a tablet. The ScanCap prototype capsule was used to image the oral mucosa in normal volunteers and ex vivo esophageal resections; images were compared to those obtained using an Olympus CV-180 endoscope. Images of superficial capillaries in intact oral mucosa were clearly visible in ScanCap images. Diagnostically relevant features of BE, including irregular Z-lines, distorted mucosa, and dilated vasculature, were clearly visible in ScanCap images of ex vivo esophageal specimens.
Line-scanning confocal microendoscope for nuclear morphometry imaging
(SPIE, 2017) Tang, Yubo; Carns, Jennifer; Richards-Kortum, Rebecca R.; Bioengineering
Fiber-optic endomicroscopy is a minimally invasive method to image cellular morphology in vivo. Using a coherent fiber bundle as an image relay, it allows additional imaging optics to be placed at the distal end of the fiber outside the body. In this research, we use this approach to demonstrate a compact, low-cost line-scanning confocal fluorescence microendoscope that can be constructed for <$5000 . Confocal imaging is enabled without the need for mechanical scanning by synchronizing a digital light projector with the rolling shutter of a CMOS camera. Its axial performance is characterized in comparison with a nonscanned high-resolution microendoscope. We validate the optical sectioning capability of the microendoscope by imaging a two-dimensional phantom and ex vivo mouse esophageal and colon tissues. Results show that optical sectioning using this approach improves visualization of nuclear morphometry and suggest that this low-cost line-scanning microendoscope can be used to evaluate various pathological conditions.
Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract
(2017-04-19) Tang, Yubo; Richards-Kortum, Rebecca
Gastrointestinal (GI) cancers impose an enormous burden on the society worldwide and a significant proportion of this burden can be prevented through early cancer detection and treatment. Current screening and surveillance protocols rely primarily on conventional white light endoscopy, the accuracy and efficacy of which need to be improved. The main objective of this research is to develop and optimize novel multi-scale optical imaging modalities to improve detection of GI cancers with enhanced imaging performance and increased clinical ease of use at a low cost. A modular video endoscope (MVE) was developed to combine widefield with high-resolution imaging modalities. Trimodal imaging, including standard white light imaging (WLI), vital-dye fluorescence imaging (VFI) and high-resolution microendoscopy (HRME), was enabled in a single endoscopic insertion. A pilot in vivo clinical trial showed that glandular architectural dysregulation, as visualized in VFI and HRME, was associated with cancer progression in Barrett’s esophagus (BE). The MVE/HRME platform was further evaluated for gastric cancer detection. In both ex vivo and in vivo pilot studies, early cancers were found to be highlighted by alterations in glandular patterns and nuclear morphology in VFI and HRME. Preliminary data in the in vivo trial showed that the platform may be useful to detect additional advanced lesions, but suggested that the specificity needs to be improved. A low-cost confocal HRME was developed to improve the axial performance of HRME with optical sectioning. By synchronizing a digital light projector (DLP) with the rolling shutter of a CMOS sensor, line-scanning confocal imaging was enabled in a compact design. Initial ex vivo validation in imaging squamous and columnar epithelium of mouse specimens demonstrated that optical sectioning improved the visualization of nuclear morphometry, especially in crowded regions with degraded image quality using a conventional HRME. Automated analysis of HRME images was also explored to facilitate its clinical applications. In 58 in vivo colorectal HRME images, a set of clinically relevant features were quantified. A 3-feature model was developed through linear discriminant analysis to achieve a sensitivity and specificity of 91% and 89%, and an AUC of 0.94 in classification of neoplastic from non-neoplastic polyps. The unique contributions of this research are the development of multi-scale imaging modalities with enhanced imaging performance and improved clinical ease of use. Computer-aided interpretation of clinical data was also investigated. These results can potentially contribute to improved early GI cancer detection, especially in community and low-resource settings.
Multimodal optical imaging with real-time projection of cancer risk and biopsy guidance maps for early oral cancer diagnosis and treatment
(SPIE, 2023) Coole, Jackson B.; Brenes, David R.; Mitbander, Ruchika; Vohra, Imran S.; Hou, Huayu; Kortum, Alex; Tang, Yubo; Maker, Yajur; Schwarz, Richard A.; Carns, Jennifer L.; Badaoui, Hawraa; Williams, Michelle D.; Vigneswaran, Nadarajah; Gillenwater, Ann M.; Richards-Kortum, Rebecca; Bioengineering
Significance: Despite recent advances in multimodal optical imaging, oral imaging systems often do not provide real-time actionable guidance to the clinician who is making biopsy and treatment decisions. Aim: We demonstrate a low-cost, portable active biopsy guidance system (ABGS) that uses multimodal optical imaging with deep learning to directly project cancer risk and biopsy guidance maps onto oral mucosa in real time. Approach: Cancer risk maps are generated based on widefield autofluorescence images and projected onto the at-risk tissue using a digital light projector. Microendoscopy images are obtained from at-risk areas, and multimodal image data are used to calculate a biopsy guidance map, which is projected onto tissue.ResultsRepresentative patient examples highlight clinically actionable visualizations provided in real time during an imaging procedure. Results show multimodal imaging with cancer risk and biopsy guidance map projection offers a versatile, quantitative, and precise tool to guide biopsy site selection and improve early detection of oral cancers. Conclusions: The ABGS provides direct visible guidance to identify early lesions and locate appropriate sites to biopsy within those lesions. This represents an opportunity to translate multimodal imaging into real-time clinically actionable visualizations to help improve patient outcomes.
Optical imaging technologies for in vivo cancer detection in low-resource settings
(Elsevier, 2023) Hou, Huayu; Mitbander, Ruchika; Tang, Yubo; Azimuddin, Ahad; Carns, Jennifer; Schwarz, Richard A.; Richards-Kortum, Rebecca R.; Bioengineering
Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and accurate cancer detection at the point of care, have great potential to improve global cancer care. This article reviews the recent technical innovations and clinical translation of low-cost optical imaging technologies, highlighting the advances in both hardware and software, especially the integration of artificial intelligence, to improve in vivo cancer detection in low-resource settings. Additionally, this article provides an overview of existing challenges and future perspectives of adapting optical imaging technologies into clinical practice, which can potentially contribute to novel insights and programs that effectively improve cancer detection in low-resource settings.
Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps
(SPIE, 2018) Tang, Yubo; Polydorides, Alexandros D.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca R.; Bioengineering
Colonoscopy is routinely performed for colorectal cancer screening but lacks the capability to accurately characterize precursor lesions and early cancers. High-resolution microendoscopy (HRME) is a low-cost imaging tool to visualize colorectal polyps with subcellular resolution. We present a computer-aided algorithm to evaluate HRME images of colorectal polyps and classify neoplastic from benign lesions. Using histopathology as the gold standard, clinically relevant features based on luminal morphology and texture are quantified to build the classification algorithm. We demonstrate that adenomatous polyps can be identified with a sensitivity and specificity of 100% and 80% using a two-feature linear discriminant model in a pilot test set. The classification algorithm presented here offers an objective framework to detect adenomatous lesions in the colon with high accuracy and can potentially improve real-time assessment of colorectal polyps.
Simple differential digital confocal aperture to improve axial response of line-scanning confocal microendoscopes
(Optical Society of America, 2019) Tang, Yubo; Kortum, Alex; Vohra, Imran; Carns, Jennifer; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca; Bioengineering
Line-scanning confocal microendoscopy offers video-rate cellular imaging of scattering tissue with relatively simple hardware, but its axial response is inferior to that of point-scanning systems. Based on Fourier optics theory, we designed differential confocal apertures with a simple subtraction technique to improve the line-scanning sectioning performance. Taking advantage of digital slit apertures on a digital light projector and a CMOS rolling shutter, we demonstrate real-time optical sectioning performance comparable to point scanning in a dual-camera microendoscope (<$6,000). We validate the background rejection capability when imaging porcine columnar epithelium stained with fluorescent contrast agents with different uptake mechanisms and staining properties.

Browsing by Author "Tang, Yubo"

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