LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear
The abnormal growth of leukocytes causes hematologic malignancies such as leukemia.
The clinical assessment methods for the diagnosis of the disease are labor-intensive and …
The clinical assessment methods for the diagnosis of the disease are labor-intensive and …
Automated classification of acute leukemia on a heterogeneous dataset using machine learning and deep learning techniques
Today, artificial intelligence and deep learning techniques constitute a prominent part in the
area of medical sciences. These techniques help doctors detect diseases early and reduce …
area of medical sciences. These techniques help doctors detect diseases early and reduce …
[HTML][HTML] Automated segmentation of leukocyte from hematological images—a study using various CNN schemes
Medical images play a fundamental role in disease screening, and automated evaluation of
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
Improved Otsu and Kapur approach for white blood cells segmentation based on LebTLBO optimization for the detection of Leukemia.
The diagnosis of leukemia involves the detection of the abnormal characteristics of blood
cells by a trained pathologist. Currently, this is done manually by observing the …
cells by a trained pathologist. Currently, this is done manually by observing the …
Modified dominance-based soft set approach for feature selection
Big data analysis applications in the field of medical image processing have recently
increased rapidly. Feature reduction plays a significant role in eliminating irrelevant features …
increased rapidly. Feature reduction plays a significant role in eliminating irrelevant features …
Segmentation and classification of lymphoblastic leukaemia using quantum neural network
In lymphoblastic leukaemia (ALL), the bone marrow naturally produces immature cells. Each
year ALL is diagnosed with over 6500 instances, and the trend is still going upward …
year ALL is diagnosed with over 6500 instances, and the trend is still going upward …
Analysis of blood cancer using microscopic image processing
H Kuresan, J Sabastian Satish… - Soft Computing and Signal …, 2022 - Springer
Blood cancer or leukemia is the cancer which leads to abnormal formation of white blood
cells in the blood by the blood marrow; it can be fatal disease if not diagnosed early. It can …
cells in the blood by the blood marrow; it can be fatal disease if not diagnosed early. It can …
Multi class classification of acute leukemia using transfer learning
A Abhishek, N Santhanam, RK Jha… - … for Advancement in …, 2022 - ieeexplore.ieee.org
Leukemia is a fatal disease which affects blood cells. Detection of this disease using
machine learning and deep learning techniques can reduce the burden of doctors and …
machine learning and deep learning techniques can reduce the burden of doctors and …
Optimised feature selection for identification of carcinogenic leukocytes using weighted aggregation based transposition PSO
S Kar, K Das Sharma, M Maitra - IETE Journal of Research, 2022 - Taylor & Francis
In this paper, an automated leukocyte identification and classification methodology using
microscopic blood smear images is proposed. After performing a colour based clustering for …
microscopic blood smear images is proposed. After performing a colour based clustering for …
Comparison of Different Deep CNN Models for Leukemia Diagnosis
C Agarwal, VP Vishwakarma - … of the International Conference on Cognitive …, 2022 - Springer
Deep learning has been gaining popularity as one of the most fascinating fields in the
technology domain. Training deep learning models from scratch encounters several …
technology domain. Training deep learning models from scratch encounters several …