Application of vibrational spectroscopy and imaging to point-of-care medicine: a review

S Pahlow, K Weber, J Popp, BR Wood… - Applied …, 2018 - journals.sagepub.com
Vibrational spectroscopy and imaging promise molecular information that can be rapidly
acquired without the need for specialized stains or dyes, thereby potentially simplifying and …

Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks

S Berisha, M Lotfollahi, J Jahanipour, I Gurcan… - Analyst, 2019 - pubs.rsc.org
Current methods for cancer detection rely on tissue biopsy, chemical labeling/staining, and
examination of the tissue by a pathologist. Though these methods continue to remain the …

Colon cancer grading using infrared spectroscopic imaging-based deep learning

S Tiwari, K Falahkheirkhah, G Cheng… - Applied …, 2022 - journals.sagepub.com
Tumor grade assessment is critical to the treatment of cancers. A pathologist typically
evaluates grade by examining morphologic organization in tissue using hematoxylin and …

Digital staining of high-definition Fourier transform infrared (FT-IR) images using deep learning

M Lotfollahi, S Berisha, D Daeinejad… - Applied …, 2019 - journals.sagepub.com
Histological stains, such as hematoxylin and eosin (H&E), are routinely used in clinical
diagnosis and research. While these labels offer a high degree of specificity, throughput is …

Rapid identification of goblet cells in unstained colon thin sections by means of quantum cascade laser-based infrared microspectroscopy

N Kröger-Lui, N Gretz, K Haase, B Kränzlin… - Analyst, 2015 - pubs.rsc.org
Changes in the volume covered by mucin-secreting goblet cell regions within colon thin
sections may serve as a means to differentiate between ulcerative colitis and infectious …

An improved machine learning-based prediction framework for early detection of events in heart failure patients using mHealth

D Kumar, K Balraj, S Seth, S Vashista, M Ramteke… - Health and …, 2024 - Springer
Purpose Acute decompensated heart failure (ADHF) is the most prevalent cause of acute
respiratory distress worldwide, accounting for the majority of new cases and associated …

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

S Ritschar, E Schirmer, B Hufnagl, MGJ Löder… - Histochemistry and cell …, 2022 - Springer
Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue
integrity and the effects at the molecular level in organisms is of increasing interest due to …

Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging

R Mankar, MJ Walsh, R Bhargava, S Prasad… - Analyst, 2018 - pubs.rsc.org
Tissue histology utilizing chemical and immunohistochemical labels plays an important role
in biomedicine and disease diagnosis. Recent research suggests that mid-infrared (IR) …

[HTML][HTML] DAX-Net: A dual-branch dual-task adaptive cross-weight feature fusion network for robust multi-class cancer classification in pathology images

DC Bui, B Song, K Kim, JT Kwak - Computer Methods and Programs in …, 2024 - Elsevier
Abstract Background and Objective Multi-class cancer classification has been extensively
studied in digital and computational pathology due to its importance in clinical decision …

[HTML][HTML] Breast cancer histopathology using infrared spectroscopic imaging: The impact of instrumental configurations

S Mittal, TP Wrobel, M Walsh, A Kajdacsy-Balla… - Clinical …, 2021 - Elsevier
Digital analysis of cancer specimens using spectroscopic imaging coupled to machine
learning is an emerging area that links spatially localized spectral signatures to tissue …