Article
Biology
Md Ziaul Hoque, Anja Keskinarkaus, Pia Nyberg, Taneli Mattila, Tapio Seppanen
Summary: Medical image registration and fusion is an effective application for disease tracking and treatment decision-making. However, challenges such as image appearance variations and large image size exist in digital pathology. In this paper, a whole slide image registration algorithm is proposed, which utilizes adaptive smoothing and feature matching to improve matching accuracy.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Medicine, General & Internal
Min Du, Yu-Meng Cai, Yu-Lei Yin, Li Xiao, Yuan Ji
Summary: This study aims to evaluate the prognostic significance of tumor-infiltrating lymphocytes (TILs) in H&E-stained slides of hepatocellular carcinoma (HCC). The results indicate that HCC patients with high infiltrating lymphocytes tend to have a lower recurrence rate and less microvascular invasion.
WORLD JOURNAL OF CLINICAL CASES
(2022)
Article
Chemistry, Multidisciplinary
Tasleem Kausar, Adeeba Kausar, Muhammad Adnan Ashraf, Muhammad Farhan Siddique, Mingjiang Wang, Muhammad Sajid, Muhammad Zeeshan Siddique, Anwar Ul Haq, Imran Riaz
Summary: This paper presents a novel machine learning-based model, called SA-GAN, for color stain normalization in histopathology images. The model is trained using the distributions of the entire dataset and the color statistics of a single target image. Evaluation results on four different histopathology datasets demonstrate the effectiveness of SA-GAN in acclimating stain contents and enhancing normalization quality. Additionally, the proposed method achieves a 6.9% improvement in accuracy for multiclass cancer type classification.
APPLIED SCIENCES-BASEL
(2022)
Article
Multidisciplinary Sciences
Kevin de Haan, Yijie Zhang, Jonathan E. Zuckerman, Tairan Liu, Anthony E. Sisk, Miguel F. P. Diaz, Kuang-Yu Jen, Alexander Nobori, Sofia Liou, Sarah Zhang, Rana Riahi, Yair Rivenson, W. Dean Wallace, Aydogan Ozcan
Summary: A method for digitally transforming H&E stained tissue into special stains was introduced, showing improved diagnosis over using H&E only. Computational stain transformation from H&E to special stains demonstrated utility in improving diagnoses of non-neoplastic kidney diseases, providing time and cost savings.
NATURE COMMUNICATIONS
(2021)
Article
Nutrition & Dietetics
Anqi Lin, Chang Qi, Mujiao Li, Rui Guan, Evgeny N. Imyanitov, Natalia V. Mitiushkina, Quan Cheng, Zaoqu Liu, Xiaojun Wang, Qingwen Lyu, Jian Zhang, Peng Luo
Summary: This study provides new insights into survival prediction for colorectal cancer patients by analyzing the lipid microenvironment, immune cell scores, and utilizing deep learning methods.
FRONTIERS IN NUTRITION
(2022)
Article
Anatomy & Morphology
Flavio Santos da Silva, Natalia Caroline Santos Aquino de Souza, Marcus Vinicius de Moraes, Bento Joao Abreu, Moacir Franco de Oliveira
Summary: The study presents a macro called CmyoSize, which accurately measures the transnuclear cross-sectional size of cardiomyocytes in H&E images. It is a fully automated and standardized method that achieves high precision and is much faster than manual tracing. The results show that CmyoSize is feasible, accurate, and time-efficient for cardiomyocyte size quantification.
ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER
(2022)
Article
Medicine, General & Internal
Mohamed Abdel-Nasser, Vivek Kumar Singh, Ehab Mahmoud Mohamed
Summary: This article proposes an efficient staining-invariant nuclei segmentation method based on self-supervised contrastive learning and a weighted hybrid dilated convolution block. The method handles the challenges of staining variations and variations in nuclei shapes and sizes in H&E whole slide imaging. The proposed approach outperforms existing methods in multiple challenging WSI datasets without the need for stain color normalization.
Article
Spectroscopy
Hesham Salem, Fatma A. Abo Elsoud, Dina Heshmat
Summary: This study introduces a simple and effective spectrofluorometric method for the analysis of fingolimod hydrochloride (FIN). The validated technique shows the ability to accurately determine the concentration of FIN in various samples, meeting the requirements of relevant regulations.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Biochemical Research Methods
Tanwi Biswas, Hiroyuki Suzuki, Masahiro Ishikawa, Naoki Kobayashi, Takashi Obi
Summary: This study proposes a deep-learning-based method for the generation of RGB EVG stained tissue from hyperspectral H&E stained one, in order to save time and cost of the conventional EVG staining procedure. The experimental results demonstrate the effectiveness of the proposed method in generating realistic RGB EVG stained image from hyperspectral H&E stained one, using a specially designed set of three basis functions.
JOURNAL OF BIOMEDICAL OPTICS
(2023)
Article
Biology
Amirreza Mahbod, Gerald Schaefer, Benjamin Bancher, Christine Loew, Georg Dorffner, Rupert Ecker, Isabella Ellinger
Summary: This paper introduces CryoNuSeg, the first fully annotated FS-derived cryosectioned and H&E-stained nuclei instance segmentation dataset, containing images from 10 human organs with three manual mark-ups for measuring intraobserver and inter-observer variabilities. The effects of tissue fixation/embedding protocol on automatic nuclei instance segmentation performance are investigated, providing a baseline segmentation benchmark for future research. The dataset and detailed information are available to researchers at https://github.com/masih4/CryoNuSeg.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Oncology
Chang Bian, Yu Wang, Zhihao Lu, Yu An, Hanfan Wang, Lingxin Kong, Yang Du, Jie Tian
Summary: Deep learning-based computational frameworks have the potential to analyze spatial distribution of immune and cancer cells in the tumor microenvironment, detect gene mutations efficiently, and provide comprehensive information for cancer therapy optimization.
Article
Multidisciplinary Sciences
Benjamin Liechty, Zhuoran Xu, Zhilu Zhang, Cheyanne Slocum, Cagla D. D. Bahadir, Mert R. R. Sabuncu, David J. J. Pisapia
Summary: This study compares the ability of expert neuropathologists and machine learning models to predict IDH mutation status in histopathology slides of infiltrating gliomas. The study finds that the errors made by neuropathologists and ML models are different, and a hybrid model combining human and ML predictions demonstrates predictive performance comparable to expert neuropathologists.
SCIENTIFIC REPORTS
(2022)
Article
Biology
Qiang Wang, Susan Fernandes, Gareth O. S. Williams, Neil Finlayson, Ahsan R. Akram, Kevin Dhaliwal, James R. Hopgood, Marta Vallejo
Summary: Using unsupervised image-to-image synthesis, this study proposes an improved co-registration method applicable to autofluorescence lifetime images at different emission wavelengths. The method shows significant superiority in co-registration and enables rapid identification of lung cancer and cellular-level characterization of cell variants.
COMMUNICATIONS BIOLOGY
(2022)
Article
Oncology
Deepak Anand, Kumar Yashashwi, Neeraj Kumar, Swapnil Rane, Peter H. Gann, Amit Sethi
Summary: The study utilized weakly supervised learning to train a DNN model for predicting a specific mutational status without requiring regional annotations, achieving high predictive accuracy. A visualization technique was also developed to accurately highlight the most informative regions, moving towards explainable artificial intelligence.
JOURNAL OF PATHOLOGY
(2021)
Article
Oncology
Eva Y. W. Cheung, Ricky W. K. Wu, Albert S. M. Li, Ellie S. M. Chu
Summary: This study identified 12 GLCM and 3 GLRLM image features that can aid in the diagnosis of GBM. Among the five models built, the SVM model demonstrated excellent accuracy, with very good sensitivity and specificity, suggesting potential clinical application for GBM diagnosis in the future.
Article
Biochemistry & Molecular Biology
Francisco J. C. Pereira, Alexandre Teixeira, Jian Kong, Cristina Barbosa, Ana Luisa Silva, Ana Marques-Ramos, Stephen A. Liebhaber, Luisa Romao
NUCLEIC ACIDS RESEARCH
(2015)
Article
Biochemistry & Molecular Biology
Ana Marques-Ramos, Marco M. Candeias, Juliane Menezes, Rafaela Lacerda, Margaret Willcocks, Alexandre Teixeira, Nicolas Locker, Luisa Romao
Article
Cell Biology
A. Gomes, P. Amaral, R. Santos, S. Santos, F. Tortosa, P. Mendonca, A. Marques-Ramos
HISTOCHEMISTRY AND CELL BIOLOGY
(2020)
Review
Environmental Sciences
Marina Almeida-Silva, Jessica Cardoso, Catarina Alemao, Sara Santos, Ana Monteiro, Vitor Manteigas, Ana Marques-Ramos
Summary: According to WHO, air quality is crucial for human health and well-being, with air pollution contributing to severe respiratory diseases. The size of aerosol particles can have adverse health effects.
Review
Environmental Sciences
Fabiana Clerigo, Sandra Ferreira, Carina Ladeira, Ana Marques-Ramos, Marina Almeida-Silva, Luis Andre Mendes
Summary: Emerging contaminants such as nanoplastics and plasticizers have gained global attention due to their limited biodegradability and potential impact on human health, especially respiratory tissue. In vitro cell culture techniques are crucial for studying the toxic effects and mechanisms of these contaminants. From the selected studies, it was observed that cell viability was the most frequently assessed endpoint and that most studies focused on epithelial cells and exposure to polystyrene. Exposure to nanoplastics or plasticizers induced dose-dependent cytotoxicity, regardless of nanoparticle size. Furthermore, nanoparticle characteristics can affect the toxic response by promoting association with other organic compounds.