Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Detalhes bibliográficos
Principais autores:	Chowdhury, Himadri, Banik, Shounak, Hossain, Arafat, Khaled, Md. Imran
Outros Autores:	Chakrabarty, Amitabha
Formato:	Tese
Idioma:	English
Publicado em:	BRAC University 2019
Assuntos:	Cancer Chronic Lymphocytic Leukemia Image processing Machine learning Machine learning.
Acesso em linha:	http://hdl.handle.net/10361/11418

Registros relacionados

A review on Bruton's Tyrosine Kinase inhibitors to outline the scopes of further advancements in the treatment of cancer
por: Khan, Muidul Hasan
Publicado em: (2024)

A review on bispecific antibody (blinatumomab) for the treatment of acute lymphoblastic leukemia
por: Choki, Kinley
Publicado em: (2024)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
por: Shawan, Naveed Rahman, et al.
Publicado em: (2019)

Machine learning as an indicator for breast cancer prediction
por: Shadman, Tahsin Mohammed, et al.
Publicado em: (2019)

Prostate cancer detection using deep learning neural network with transfer learning approach
por: Badhon, Ariful Islam Mahmud, et al.
Publicado em: (2022)

An efficient deep learning approach to detect skin Cancer
por: Islam, Ashfaqul, et al.
Publicado em: (2022)

Vision Transformer (ViT) approach in computer aided diagnosis of acute lymphoblastic leukemia
por: Amin, Sifatul, et al.
Publicado em: (2023)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
por: Sakir, Adnan, et al.
Publicado em: (2023)

Prediction of acute lymphoid leukemia using Privacy Preserving Neural Network
por: Khilji, Ishfaque Qamar, et al.
Publicado em: (2021)

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
por: Sakib, Hasibul, et al.
Publicado em: (2024)

Identification of childhood leukemia using deep learning
por: Tultul, Farana Naz
Publicado em: (2018)

Breast cancer prediction using different machine learning models
por: Khandker Al- Muhaimin, et al.
Publicado em: (2020)

An efficient ML approach to detect brain tumor using MRI images
por: Muktadir, MD. Arafat, et al.
Publicado em: (2024)

Early detection of breast cancer using machine learning
por: Fuad, Wasi Mohammad
Publicado em: (2019)

Detection of skin cancer using Convolutional neural network
por: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, et al.
Publicado em: (2020)

Corn leaf disease detection using deep convolution neural network
por: Rabbi, Rawhatur, et al.
Publicado em: (2023)

Fake profile detection in social media using image processing and machine learning
por: Sen, Shuva, et al.
Publicado em: (2021)

Detecting propagandistic poster title: a machine learning approach
por: Mahmood, Riaz, et al.
Publicado em: (2024)

RetinalNet-500: a newly developed CNN model for eye disease detection
por: Toki, Sadikul Alim, et al.
Publicado em: (2023)

Heart disease prediction using machine learning algorithms
por: Ali, Musfiq, et al.
Publicado em: (2019)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
por: Sharma, Tanmoyee, et al.
Publicado em: (2021)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
por: Nawrin, Ishrat Nur, et al.
Publicado em: (2023)

Lung cancer detection and classification using machine learning
por: Arefin, Mahbubul, et al.
Publicado em: (2023)

Determining fatal heart failure risks in patients diagnosed with chronic kidney disease: a machine learning approach
por: Haque, Adiba, et al.
Publicado em: (2022)

A machine learning approach to detect depression and anxiety using supervised learning
por: Ullas, Md Tahmidur Rahman, et al.
Publicado em: (2019)

Cancer classification using deep learning from medical image data
por: Monir, Raiyan Janik, et al.
Publicado em: (2022)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
por: Alhossen, Md., et al.
Publicado em: (2021)

An implementation and analysis of deep learning models for the detection of wheat diseases
por: Zubair, Ahmad, et al.
Publicado em: (2024)

Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study
por: Faisal, Shah
Publicado em: (2024)

Using deep learning algorithms to detect violent activities
por: Ammar, S.M. Rojin, et al.
Publicado em: (2019)

Advances in Chronic Lymphocytic Leukemia
Publicado em: (2013)

Application of CNN based architectures in detection of distracted drivers
por: Arafin, Irfana, et al.
Publicado em: (2023)

A modern technique to detect potholes by Computer Vision and Deep Learning
por: Saif, Muntasir Mahmud, et al.
Publicado em: (2023)

Real-time foul detection in football matches using machine learning techniques
por: Siddiqui, Bishal Sadi, et al.
Publicado em: (2024)

Skin cancer classification for seven types of skin lesions
por: Rahman, Md. Tawsifur, et al.
Publicado em: (2024)

Detection of common thorax diseases from X-Ray images using a fusion of transfer and statistical learning method
por: Rafi, Ahmad Abdur, et al.
Publicado em: (2023)

Analysis of deep learning models on low-light pest detection
por: Irtiza, Md. Samin, et al.
Publicado em: (2023)

Public vehicle ETA system using machine learning
por: Kabir, Md. Miraz, et al.
Publicado em: (2018)

Predicting depression in Bangladeshi undergraduates using machine learning
por: Choudhury, Ahnaf Atef, et al.
Publicado em: (2019)

Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
por: Ahmed, Yasin, et al.
Publicado em: (2018)