An integrated iterative annotation technique for easing neural network training in medical image analysis
Neural networks promise to bring robust, quantitative analysis to medical fields. However,
their adoption is limited by the technicalities of training these networks and the required …
their adoption is limited by the technicalities of training these networks and the required …
Identifying and Counting Avian Blood Cells in Whole Slide Images via Deep Learning
Simple Summary Avian blood analysis is crucial for understanding the health of birds.
Currently, avian blood cells are often counted manually in microscopic images, which is time …
Currently, avian blood cells are often counted manually in microscopic images, which is time …
Efficient detection and partitioning of overlapped red blood cells using image processing approach
Detecting the abnormality of Red Blood Cells automatically aids hematologists in
diagnosing sickness and minimizes time, money. The complicated background, noise …
diagnosing sickness and minimizes time, money. The complicated background, noise …
ESGs and SDGs
Lately, there has been a growing recognition of the significance of environmental, social,
and corporate governance (ESG) principles across diverse industry sectors, particularly in …
and corporate governance (ESG) principles across diverse industry sectors, particularly in …
Morphological Abnormalities Classification of Red Blood Cells Using Fusion Method on Imbalance Datasets
Red blood cells (RBCs) or Erythrocytes are essential components of the human body and
they transport oxygen O 2\left (O _2\right) from the lungs to the body's tissues, regulate pH …
they transport oxygen O 2\left (O _2\right) from the lungs to the body's tissues, regulate pH …
Red and white blood cell classification using Artificial Neural Networks
S Çelebi, M Burkay Çöteli - 2018 - open.metu.edu.tr
Blood cell classification is a recent topic for scientists working on the diagnosis of blood cell
related illnesses. As the number of computer vision (CV) applications is increasing to …
related illnesses. As the number of computer vision (CV) applications is increasing to …
Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis
Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption
is limited by the technicalities of training these networks. To address this translation gap …
is limited by the technicalities of training these networks. To address this translation gap …
Application of deep learning based methodology for the optimisation of monolayer classification and white blood cell localisation in avian blood samples
E Andersdotter - 2024 - lup.lub.lu.se
Current automated haematology systems lack the functionality of avian blood analysis using
10x magnification, which is an important feature as it allows for faster and more cost-effective …
10x magnification, which is an important feature as it allows for faster and more cost-effective …
Improving the Efficiency for Segmentation of Gigapixel Sized Digital Pathology Whole Slide Images
BR Lutnick - 2022 - search.proquest.com
Recent advances in automated image recognition techniques (particularly convolutional
neural networks, CNNs) have found applications for the analysis of histopathology slides …
neural networks, CNNs) have found applications for the analysis of histopathology slides …
Exploring Endoparasites and Physiological Stress: Insights from a European Forest Bird Community
F Strehmann - archiv.ub.uni-marburg.de
The global biodiversity crisis is advancing steadily. Additionally, climate change increases
the risk of emerging infectious diseases (EIDs). Due to their global migration, birds are of …
the risk of emerging infectious diseases (EIDs). Due to their global migration, birds are of …