A systematic review on recent advancements in deep and machine learning based detection and classification of acute lymphoblastic leukemia
Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …
required in healthcare centers. It has a significant role in early diagnosis and treatment …
[HTML][HTML] Recent computational methods for white blood cell nuclei segmentation: A comparative study
AR Andrade, LHS Vogado, R de MS Veras… - Computer methods and …, 2019 - Elsevier
Background and objective: Leukaemia is a disease found worldwide; it is a type of cancer
that originates in the bone marrow and is characterised by an abnormal proliferation of white …
that originates in the bone marrow and is characterised by an abnormal proliferation of white …
An automatic nucleus segmentation and CNN model based classification method of white blood cell
White blood cells (WBCs) play a remarkable role in the human immune system. To diagnose
blood-related diseases, pathologists need to consider the characteristics of WBC. The …
blood-related diseases, pathologists need to consider the characteristics of WBC. The …
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 …
Recognition of acute lymphoblastic leukemia cells in microscopic images using k-means clustering and support vector machine classifier
Acute lymphoblastic leukemia is the most common form of pediatric cancer which is
categorized into three L1, L2, and L3 and could be detected through screening of blood and …
categorized into three L1, L2, and L3 and could be detected through screening of blood and …
Automated screening system for acute myelogenous leukemia detection in blood microscopic images
S Agaian, M Madhukar… - IEEE Systems …, 2014 - ieeexplore.ieee.org
Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is prevalent
among adults. The average age of a person with AML is 65 years. The need for automation …
among adults. The average age of a person with AML is 65 years. The need for automation …
An intelligent decision support system for leukaemia diagnosis using microscopic blood images
This research proposes an intelligent decision support system for acute lymphoblastic
leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with …
leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with …
A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images
Computer‐based imaging systems are becoming important tools for quantitative assessment
of peripheral blood and bone marrow samples to help experts diagnose blood disorders …
of peripheral blood and bone marrow samples to help experts diagnose blood disorders …
Detection of leukemia and its types using image processing and machine learning
P Jagadev, HG Virani - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
Leukemia (blood cancer) begins in the bone marrow and causes the formation of a large
number of abnormal cells. The most common types of leukemia known are Acute …
number of abnormal cells. The most common types of leukemia known are Acute …
Automatic recognition of acute myelogenous leukemia in blood microscopic images using k-means clustering and support vector machine
Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is characterized
by the accumulation of myeloid blasts in the bone marrow. Careful microscopic examination …
by the accumulation of myeloid blasts in the bone marrow. Careful microscopic examination …