Article
Engineering, Electrical & Electronic
Satya Prasanna Mallick, K. S. Adithya, Ratul Sabui, Balu Babu Naidu, Ranjeet Singh, Harish Babu, Gajula Jagadeesh, K. M. Venkata Amaresh, Ram Gopal, Vandana Sharma
Summary: We propose a novel approach to whole slide imaging (WSI) using a low-cost, portable, fully enclosed scanner device that can be controlled wirelessly through an intuitive user interface on an iPad. The device incorporates features such as automatic slide loading, brightness control, and an autofocus algorithm.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Biochemical Research Methods
Shaowei Jiang, Chengfei Guo, Pengming Song, Tianbo Wang, Ruihai Wang, Terrance Zhang, Qian Wu, Rishikesh Pandey, Guoan Zheng
Summary: The recent advent of whole slide imaging systems has brought digital pathology closer to diagnostic applications and clinical practices. Integrating whole slide imaging with machine learning promises growth in this field. This study reports the design and implementation of a handheld, colour-multiplexed, and AI-powered ptychographic whole slide scanner for digital pathology applications.
Article
Microbiology
Maximilian W. D. Raas, Thiago P. Silva, Jhamine C. O. Freitas, Lara M. Campos, Rodrigo L. Fabri, Rossana C. N. Melo
Summary: The study utilized whole slide imaging (WSI) to visualize Candida biofilm formation, staining accumulated biofilms with fluorescent markers and scanning in both bright-field and fluorescence modes using a WSI digital scanner. WSI allowed for clear assessment of biofilm size and structural features, with quantitative analysis showing reductions in biofilm-covered surface area upon antifungal exposure. At the single-cell level, WSI proved to be adequate for evaluating morphometric parameters, demonstrating its reliability in visualizing Candida biofilms and making it an important addition to microscopic tools for fungal biofilm growth analysis.
MICROBIOLOGICAL RESEARCH
(2021)
Article
Pathology
Shizu Shinohara, Andrey Bychkov, Jijgee Munkhdelger, Kishio Kuroda, Han-Seung Yoon, Shota Fujimura, Kazuhiro Tabata, Bungo Furusato, Daisuke Niino, Shinpei Morimoto, Takashi Yao, Tomoo Itoh, Hajime Aoyama, Naoko Tsuyama, Yoshiki Mikami, Toshitaka Nagao, Tohru Ikeda, Noriyoshi Fukushima, Oi Harada, Takako Kiyokawa, Naoki Yoshimi, Shinichi Aishima, Ichiro Maeda, Ichiro Mori, Koji Yamanegi, Koichi Tsuneyama, Ryohei Katoh, Miki Izumi, Yoshinao Oda, Junya Fukuoka
Summary: This study investigated the diagnostic benefits of remote consultation using whole-slide images for challenging pathological cases. The results showed significant improvement in pathological diagnosis through remote consultation, which can further assist in patient healthcare.
Article
Urology & Nephrology
Briana A. Santo, Darshana Govind, Parnaz Daneshpajouhnejad, Xiaoping Yang, Xiaoxin X. Wang, Komuraiah Myakala, Bryce A. Jones, Moshe Levi, Jeffrey B. Kopp, Teruhiko Yoshida, Laura J. Niedernhofer, David Manthey, Kyung Chul Moon, Seung Seok Han, Jarcy Zee, Avi Z. Rosenberg, Pinaki Sarder
Summary: A computational tool called PodoCount was developed for automated podocyte quantification in various experimental and clinical settings. The tool demonstrated high accuracy and significant correlation with disease state, proteinuria, and clinical outcome.
KIDNEY INTERNATIONAL REPORTS
(2022)
Article
Multidisciplinary Sciences
Cindy Serdjebi, Karine Bertotti, Pinzhu Huang, Guangyan Wei, Disha Skelton-Badlani, Isabelle A. Leclercq, Damien Barbes, Bastien Lepoivre, Yury Popov, Yvon Jule
Summary: This study utilized an automated image analysis software to quantitatively assess fibrosis deposition in two preclinical models of liver fibrosis and established correlations with other quantitative fibrosis descriptors. The results demonstrate that automated digital analysis is a reliable tool for evaluating the dynamics of liver fibrosis and efficacy of antifibrotic drug candidates in preclinical models.
SCIENTIFIC REPORTS
(2022)
Article
Surgery
Krsna Kothari, Joseph Okello Damoi, Nebras Zeizafoun, Penninah Asiimwe, Katie Glerum, Moses Bakaleke, Angelica Giibwa, Melissa Umphlett, Michael Marin, Linda P. Zhang
Summary: This study demonstrated the feasibility and considerations of implementing a telepathology model to supplement the critical pathology needs of a low-income country.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Biochemical Research Methods
Istvan Rebenku, Ferenc A. Bartha, Tamas Katona, Barbara Zsebik, Geza Antalffy, Lili Takacs, Bela Molnar, Gyorgy Vereb
Summary: The emergence and fast advance of digital pathology allows the acquisition, digital storage, interactive recall and analysis of tissue-level morphology. The rise of fluorescence pathology scanners expands the detection of molecules based on multiplex labeling. The Pannoramic Confocal provides sensitive, quantitative widefield and confocal detection of multiplexed fluorescence signals, with optical sectioning and 3D reconstruction.
Article
Oncology
Songhui Diao, Pingjun Chen, Eman Showkatian, Rukhmini Bandyopadhyay, Frank R. Rojas, Bo Zhu, Lingzhi Hong, Muhammad Aminu, Maliazurina B. Saad, Morteza Salehjahromi, Amgad Muneer, Sheeba J. Sujit, Carmen Behrens, Don L. Gibbons, John V. Heymach, Neda Kalhor, Ignacio I. Wistuba, Luisa M. Solis Soto, Jianjun Zhang, Wenjian Qin, Jia Wu
Summary: In this study, a fully automated cellular-level survival prediction pipeline was proposed using histopathologic images of lung adenocarcinoma. The results demonstrate meaningful, convincing, and comprehensible survival prediction ability, showcasing the potential for application to other malignancies.
Article
Computer Science, Information Systems
Amal Lahiani, Irina Klaman, Nassir Navab, Shadi Albarqouni, Eldad Klaiman
Summary: Virtual staining is a growing interest in digital pathology, allowing for simulation of stained tissue images to save resources, with the use of unsupervised style transfer GANs. A novel perceptual embedding consistency loss is proposed to reduce tiling artifacts in virtual staining, resulting in more seamless reconstruction. Quantitative validation and comparison with real stained images demonstrate the effectiveness of the proposed method.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Pathology
Charisse Liz B. Treece, Jennifer Filipek, Jitin Makker, Neda A. Moatamed, Erika F. Rodriguez
Summary: This study assessed the accuracy of remote FS consultation using digital modalities (WSI and videoconferencing) compared to in-person consultation (IPC). While videoconferencing had longer turnaround times, both WSI and videoconferencing showed equivalent accuracy to IPC. Thus, remote FS consultation through digital modalities is a safe and feasible option for complex cases.
AMERICAN JOURNAL OF CLINICAL PATHOLOGY
(2023)
Review
Pathology
Jayaram N. Iyengar
Summary: The development of whole slide scanners has led to the widespread use of digitized whole slide images in histopathology, providing new possibilities for expert consults, quality assessment, education, and routine reporting. Industry development is driven by consumer demands, resulting in significant improvements in image quality, scanning speed, file size, and equipment capital cost.
INDIAN JOURNAL OF PATHOLOGY AND MICROBIOLOGY
(2021)
Article
Pathology
Joshua E. Lewis, Conrad W. Shebelut, Bradley R. Drumheller, Xuebao Zhang, Nithya Shanmugam, Michel Attieh, Michael C. Horwath, Anurag Khanna, Geoffrey H. Smith, David A. Gutman, Ahmed Aljudi, Lee A. D. Cooper, David L. Jaye
Summary: This study developed an automated machine learning-based pipeline for obtaining 11-component differential cell counts (DCCs) on whole-slide bone marrow aspirate (BMA) images. The pipeline demonstrated a high concordance with manual DCCs and reduced intraslide variance in DCCs. It has the potential to improve the current standard practice for analyzing hematologic disorders.
Review
Oncology
Mark D. Zarella, Keysabelis Rivera Alvarez
Summary: Digital pathology and artificial intelligence rely on the digitization of patient material. Innovations in whole-slide imaging technology and automated informatics approaches have enabled high-throughput scanning, improving workflow efficiency and imaging data quality. However, challenges remain and further innovation is needed in automation and quality control to make high-throughput scanning accessible to laboratories with limited resources.
JOURNAL OF PATHOLOGY
(2022)
Article
Oncology
Yingci Liu, Elizabeth Bilodeau, Brian Pollack, Kayhan Batmanghelich
Summary: This study developed a convolutional neural network (CNN) model for identifying suspicious regions of OED in oral pathology images. The Deep-Labv3+ model outperformed the UNet++ model in OED segmentation and classification. The best performing Deep-Labv3+ model achieved high accuracy and F1-Score on the test set.
