[HTML][HTML] A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches
Microorganisms such as bacteria and fungi play essential roles in many application fields,
like biotechnique, medical technique and industrial domain. Microorganism counting …
like biotechnique, medical technique and industrial domain. Microorganism counting …
The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review
Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis
of different types of cancer. The preparation and digitization of histological tissues leads to …
of different types of cancer. The preparation and digitization of histological tissues leads to …
Vision transformers for computational histopathology
Computational histopathology is focused on the automatic analysis of rich phenotypic
information contained in gigabyte whole slide images, aiming at providing cancer patients …
information contained in gigabyte whole slide images, aiming at providing cancer patients …
Multiple attentional path aggregation network for marine object detection
H Yu, X Li, Y Feng, S Han - Applied intelligence, 2023 - Springer
Marine target detection is a challenging task because degraded underwater images cause
unclear targets. Furthermore, marine targets are small in size and tend to live together. The …
unclear targets. Furthermore, marine targets are small in size and tend to live together. The …
[HTML][HTML] Deep learning in computational dermatopathology of melanoma: A technical systematic literature review
Deep learning (DL) has become one of the major approaches in computational
dermatopathology, evidenced by a significant increase in this topic in the current literature …
dermatopathology, evidenced by a significant increase in this topic in the current literature …
MDC-net: A new convolutional neural network for nucleus segmentation in histopathology images with distance maps and contour information
Accurate segmentation of nuclei in digital pathology images can assist doctors in diagnosing
diseases and evaluating subsequent treatments. Manual segmentation of nuclei from …
diseases and evaluating subsequent treatments. Manual segmentation of nuclei from …
[HTML][HTML] Generative models for color normalization in digital pathology and dermatology: Advancing the learning paradigm
Color medical images introduce an additional confounding factor compared to conventional
grayscale medical images: color variability. This variability can lead to inconsistent …
grayscale medical images: color variability. This variability can lead to inconsistent …
[HTML][HTML] Impact of quality, type and volume of data used by deep learning models in the analysis of medical images
AR Luca, TF Ursuleanu, L Gheorghe… - Informatics in Medicine …, 2022 - Elsevier
The need for time and attention given by the doctor to the patient, due to the increased
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
[HTML][HTML] Current developments of artificial intelligence in digital pathology and its future clinical applications in gastrointestinal cancers
Simple Summary The rapid development of technology has enabled numerous applications
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …
[HTML][HTML] A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers
Abstract Within the next 1.5 decades, 1 in 7 US adults is anticipated to suffer from age-
related macular degeneration (AMD), a degenerative retinal disease which leads to …
related macular degeneration (AMD), a degenerative retinal disease which leads to …