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Lotz S, Göb M, Böttger S, Ha-Wissel L, Hundt J, Ernst F, Huber R. Large area robotically assisted optical coherence tomography (LARA-OCT). BIOMEDICAL OPTICS EXPRESS 2024; 15:3993-4009. [PMID: 38867778 PMCID: PMC11166428 DOI: 10.1364/boe.525524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 06/14/2024]
Abstract
We demonstrate large-area robotically assisted optical coherence tomography (LARA-OCT), utilizing a seven-degree-of-freedom robotic arm in conjunction with a 3.3 MHz swept-source OCT to raster scan samples of arbitrary shape. By combining multiple fields of view (FOV), LARA-OCT can probe a much larger area than conventional OCT. Also, nonplanar and curved surfaces like skin on arms and legs can be probed. The lenses in the LARA-OCT scanner with their normal FOV can have fewer aberrations and less complex optics compared to a single wide field design. This may be especially critical for high resolution scans. We directly use our fast MHz-OCT for tracking and stitching, making additional machine vision systems like cameras, positioning, tracking or navigation devices obsolete. This also eliminates the need for complex coordinate system registration between OCT and the machine vision system. We implemented a real time probe-to-surface control that maintains the probe alignment orthogonal to the sample by only using surface information from the OCT images. We present OCT data sets with volume sizes of 140 × 170 × 20 mm3, captured in 2.5 minutes.
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Affiliation(s)
- Simon Lotz
- Institute of Biomedical Optics, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
| | - Madita Göb
- Institute of Biomedical Optics, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
| | - Sven Böttger
- Institute for Robotic and Cognitive Systems, Universität zu Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
- qtec Services GmbH, Niels-Bohr-Ring 3-5, 23568 Lübeck, Germany
| | - Linh Ha-Wissel
- Lübeck Institute of Experimental Dermatology, Universität zu Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
- Department of Dermatology, Allergology, Venerology, University Hospital of Schleswig-Holstein, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Jennifer Hundt
- Lübeck Institute of Experimental Dermatology, Universität zu Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Floris Ernst
- Institute for Robotic and Cognitive Systems, Universität zu Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Robert Huber
- Institute of Biomedical Optics, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
- Medizinisches Laserzentrum Lübeck GmbH, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
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Wang Y, Wei S, Zuo R, Kam M, Opfermann JD, Sunmola I, Hsieh MH, Krieger A, Kang JU. Automatic and real-time tissue sensing for autonomous intestinal anastomosis using hybrid MLP-DC-CNN classifier-based optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2024; 15:2543-2560. [PMID: 38633079 PMCID: PMC11019703 DOI: 10.1364/boe.521652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/18/2024] [Accepted: 03/18/2024] [Indexed: 04/19/2024]
Abstract
Anastomosis is a common and critical part of reconstructive procedures within gastrointestinal, urologic, and gynecologic surgery. The use of autonomous surgical robots such as the smart tissue autonomous robot (STAR) system demonstrates an improved efficiency and consistency of the laparoscopic small bowel anastomosis over the current da Vinci surgical system. However, the STAR workflow requires auxiliary manual monitoring during the suturing procedure to avoid missed or wrong stitches. To eliminate this monitoring task from the operators, we integrated an optical coherence tomography (OCT) fiber sensor with the suture tool and developed an automatic tissue classification algorithm for detecting missed or wrong stitches in real time. The classification results were updated and sent to the control loop of STAR robot in real time. The suture tool was guided to approach the object by a dual-camera system. If the tissue inside the tool jaw was inconsistent with the desired suture pattern, a warning message would be generated. The proposed hybrid multilayer perceptron dual-channel convolutional neural network (MLP-DC-CNN) classification platform can automatically classify eight different abdominal tissue types that require different suture strategies for anastomosis. In MLP, numerous handcrafted features (∼1955) were utilized including optical properties and morphological features of one-dimensional (1D) OCT A-line signals. In DC-CNN, intensity-based features and depth-resolved tissues' attenuation coefficients were fully exploited. A decision fusion technique was applied to leverage the information collected from both classifiers to further increase the accuracy. The algorithm was evaluated on 69,773 testing A-line data. The results showed that our model can classify the 1D OCT signals of small bowels in real time with an accuracy of 90.06%, a precision of 88.34%, and a sensitivity of 87.29%, respectively. The refresh rate of the displayed A-line signals was set as 300 Hz, the maximum sensing depth of the fiber was 3.6 mm, and the running time of the image processing algorithm was ∼1.56 s for 1,024 A-lines. The proposed fully automated tissue sensing model outperformed the single classifier of CNN, MLP, or SVM with optimized architectures, showing the complementarity of different feature sets and network architectures in classifying intestinal OCT A-line signals. It can potentially reduce the manual involvement of robotic laparoscopic surgery, which is a crucial step towards a fully autonomous STAR system.
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Affiliation(s)
- Yaning Wang
- Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Shuwen Wei
- Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Ruizhi Zuo
- Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Michael Kam
- Department of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Justin D. Opfermann
- Department of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Idris Sunmola
- Department of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Michael H. Hsieh
- Division of Urology, Children’s National Hospital, 111 Michigan Ave NW, Washington, D.C. 20010, USA
| | - Axel Krieger
- Department of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Jin U. Kang
- Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA
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Ma X, Moradi M, Ma X, Tang Q, Levi M, Chen Y, Zhang HK. Large Area Kidney Imaging for Pre-transplant Evaluation using Real-Time Robotic Optical Coherence Tomography. RESEARCH SQUARE 2023:rs.3.rs-3385622. [PMID: 37886456 PMCID: PMC10602184 DOI: 10.21203/rs.3.rs-3385622/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Optical coherence tomography (OCT) is a high-resolution imaging modality that can be used to image microstructures of human kidneys. These images can be analyzed to evaluate the viability of the organ for transplantation. However, current OCT devices suffer from insufficient field-of-view, leading to biased examination outcomes when only small portions of the kidney can be assessed. Here we present a robotic OCT system where an OCT probe is integrated with a robotic manipulator, enabling wider area spatially-resolved imaging. With the proposed system, it becomes possible to comprehensively scan the kidney surface and provide large area parameterization of the microstructures. We verified the probe tracking accuracy with a phantom as 0.0762±0.0727 mm and demonstrated its clinical feasibility by scanning ex vivo kidneys. The parametric map exhibits fine vasculatures beneath the kidney surface. Quantitative analysis on the proximal convoluted tubule from the ex vivo human kidney yields highly clinical-relevant information.
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Affiliation(s)
- Xihan Ma
- Department of Robotics Engineering, Worcester Polytechnic Institute, MA 01609, USA
| | - Mousa Moradi
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
| | - Xiaoyu Ma
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
| | - Qinggong Tang
- The Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Moshe Levi
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC 20057, USA
| | - Yu Chen
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
| | - Haichong K Zhang
- Department of Robotics Engineering, Worcester Polytechnic Institute, MA 01609, USA
- Department of Biomedical Engineering, Worcester Polytechnic Institute, MA 01609, USA
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He B, Zhang Y, Zhao L, Sun Z, Hu X, Kang Y, Wang L, Li Z, Huang W, Li Z, Xing G, Hua F, Wang C, Xue P, Zhang N. Robotic-OCT guided inspection and microsurgery of monolithic storage devices. Nat Commun 2023; 14:5701. [PMID: 37709753 PMCID: PMC10502073 DOI: 10.1038/s41467-023-41498-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 09/06/2023] [Indexed: 09/16/2023] Open
Abstract
Data recovery from monolithic storage devices (MSDs) is in high demand for legal or business purposes. However, the conventional data recovery methods are destructive, complicated, and time-consuming. We develop a robotic-arm-assisted optical coherence tomography (robotic-OCT) for non-destructive inspection of MSDs, offering ~7 μm lateral resolution, ~4 μm axial resolution and an adjustable field-of-view to accommodate various MSD sizes. Using a continuous scanning strategy, robotic-OCT achieves automated volumetric imaging of a micro-SD card in ~37 seconds, significantly faster than the traditional stop-and-stare scanning that typically takes tens of minutes. We also demonstrate the robotic-OCT-guided laser ablation as a microsurgical tool for targeted area removal with precision of ±10 μm and accuracy of ~50 μm, eliminating the need to remove the entire insulating layer and operator intervention, thus greatly improving the data recovery efficiency. This work has diverse potential applications in digital forensics, failure analysis, materials testing, and quality control.
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Affiliation(s)
- Bin He
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
- State Key Laboratory of Low-dimensional Quantum Physics and Department of Physics, Tsinghua University and Beijing Advanced Innovation Center for Structural Biology, 100084, Beijing, China
| | - Yuxin Zhang
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
- State Key Laboratory of Low-dimensional Quantum Physics and Department of Physics, Tsinghua University and Beijing Advanced Innovation Center for Structural Biology, 100084, Beijing, China
| | - Lu Zhao
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Zhenwen Sun
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Xiyuan Hu
- School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, China
| | - Yanrong Kang
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Lei Wang
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Zhihui Li
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Wei Huang
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Zhigang Li
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Guidong Xing
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Feng Hua
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China
| | - Chengming Wang
- State Key Laboratory of Low-dimensional Quantum Physics and Department of Physics, Tsinghua University and Beijing Advanced Innovation Center for Structural Biology, 100084, Beijing, China
| | - Ping Xue
- State Key Laboratory of Low-dimensional Quantum Physics and Department of Physics, Tsinghua University and Beijing Advanced Innovation Center for Structural Biology, 100084, Beijing, China.
| | - Ning Zhang
- Institute of Forensic Science, Ministry of Public Security, 100038, Beijing, China.
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Li X, Huang Y, Hao Q. Automated robot-assisted wide-field optical coherence tomography using structured light camera. BIOMEDICAL OPTICS EXPRESS 2023; 14:4310-4325. [PMID: 37799682 PMCID: PMC10549741 DOI: 10.1364/boe.496710] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/07/2023] [Accepted: 07/13/2023] [Indexed: 10/07/2023]
Abstract
Optical coherence tomography (OCT) is a promising real-time and non-invasive imaging technology widely utilized in biomedical and material inspection domains. However, limited field of view (FOV) in conventional OCT systems hampers their broader applicability. Here, we propose an automated system integrating a structured light camera and robotic arm for large-area OCT scanning. The system precisely detects tissue contours, automates scan path generation, and enables accurate scanning of expansive sample areas. The proposed system consists of a robotic arm, a three-dimensional (3D) structured light camera, and a customized portable OCT probe. The 3D structured light camera is employed to generate a precise 3D point cloud of the sample surface, enabling automatic planning of the scanning path for the robotic arm. Meanwhile, the OCT probe is mounted on the robotic arm, facilitating scanning of the sample along the predetermined path. Continuous OCT B-scans are acquired during the scanning process, facilitating the generation of high-resolution and large-area 3D OCT reconstructions of the sample. We conducted position error tests and presented examples of 3D macroscopic imaging of different samples, such as ex vivo kidney, skin and leaf blade. The robotic arm can accurately reach the planned positions with an average absolute error of approximately 0.16 mm. The findings demonstrate that the proposed system enables the acquisition of 3D OCT images covering an area exceeding 20 cm2, indicating wide-ranging potential for utilization in diverse domains such as biomedical, industrial, and agricultural fields.
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Affiliation(s)
- Xiaochen Li
- School of Optics and Photonics, Beijing Institute of Technology, No.5 South Zhongguancun Street, Haidian, Beijing, 100081, China
| | - Yong Huang
- School of Optics and Photonics, Beijing Institute of Technology, No.5 South Zhongguancun Street, Haidian, Beijing, 100081, China
| | - Qun Hao
- School of Optics and Photonics, Beijing Institute of Technology, No.5 South Zhongguancun Street, Haidian, Beijing, 100081, China
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Ha-Wissel L, Yasak H, Huber R, Zillikens D, Ludwig RJ, Thaçi D, Hundt JE. Case report: Optical coherence tomography for monitoring biologic therapy in psoriasis and atopic dermatitis. Front Med (Lausanne) 2022; 9:995883. [PMID: 36237538 PMCID: PMC9551172 DOI: 10.3389/fmed.2022.995883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Biologic therapies are increasingly used to treat chronic inflammatory skin diseases such as psoriasis and atopic dermatitis. In clinical practice, scores based on evaluation of objective and subjective symptoms are used to assess disease severity, leading to evaluation of treatment goals with clinical decisions on treatment initiation, switch to another treatment modality or to discontinue current treatment. However, this visual-based scoring is relatively subjective and inaccurate due to inter- and intraobserver reliability. Optical coherence tomography (OCT) is a fast, high-resolution, in vivo imaging modality that enables the visualization of skin structure and vasculature. We evaluated the use of OCT for quantification and monitoring of skin inflammation to improve objective assessment of disease activity in patients with psoriasis and atopic dermatitis. We assessed the following imaging parameters including epidermal thickness, vascular density, plexus depth, vessel diameter, and vessel count. A total of four patients with psoriasis or atopic dermatitis were treated with biologic agents according to current treatment guidelines. OCT was used to monitor their individual treatment response in a target lesion representing disease activity for 52 weeks. Psoriatic and eczema lesions exhibited higher epidermal thickness, increased vascular density, and higher vessel count compared to uninvolved skin. An upward shift of the superficial vascular plexus accompanied by smaller vessel diameters was seen in psoriasis in contrast to atopic dermatitis, where larger vessels were observed. A response to biologic therapy was characterized by normalization of the imaging parameters in the target lesions in comparison to uninvolved skin during the observation period of 52 weeks. Optical coherence tomography potentially serves as an instrument to monitor biologic therapy in inflammatory skin diseases. Imaging parameters may enable objective quantification of inflammation in psoriasis or atopic dermatitis in selected representative skin areas. OCT may reveal persistent subclinical inflammation in atopic dermatitis beyond clinical remission.
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Affiliation(s)
- Linh Ha-Wissel
- Department of Dermatology, Allergology and Venereology, University Hospital Schleswig-Holstein Lübeck (UKSH), Lübeck, Germany
- Institute for Inflammatory Medicine, University of Lübeck, Lübeck, Germany
- *Correspondence: Linh Ha-Wissel,
| | - Handan Yasak
- Institute for Inflammatory Medicine, University of Lübeck, Lübeck, Germany
| | - Robert Huber
- Institute of Biomedical Optics, University of Lübeck, Lübeck, Germany
| | - Detlef Zillikens
- Department of Dermatology, Allergology and Venereology, University Hospital Schleswig-Holstein Lübeck (UKSH), Lübeck, Germany
| | - Ralf J. Ludwig
- Department of Dermatology, Allergology and Venereology, University Hospital Schleswig-Holstein Lübeck (UKSH), Lübeck, Germany
- Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck, Lübeck, Germany
| | - Diamant Thaçi
- Institute for Inflammatory Medicine, University of Lübeck, Lübeck, Germany
| | - Jennifer E. Hundt
- Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck, Lübeck, Germany
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Rank EA, Agneter A, Schmoll T, Leitgeb RA, Drexler W. Miniaturizing optical coherence tomography. TRANSLATIONAL BIOPHOTONICS 2022. [DOI: 10.1002/tbio.202100007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Elisabet A. Rank
- Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria
| | - Anja Agneter
- Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria
| | - Tilman Schmoll
- Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria
- Carl Zeiss Meditec, Inc. Dublin California USA
| | - Rainer A. Leitgeb
- Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria
| | - Wolfgang Drexler
- Center for Medical Physics and Biomedical Engineering Medical University of Vienna Vienna Austria
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