Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges

G Murtaza, L Shuib, AW Abdul Wahab… - Artificial Intelligence …, 2020 - Springer
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …

[Retracted] Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection

M Kamal, AR Pratap, M Naved… - Computational …, 2022 - Wiley Online Library
Alzheimer's disease is characterized by the presence of abnormal protein bundles in the
brain tissue, but experts are not yet sure what is causing the condition. To find a cure or …

A review of image processing techniques common in human and plant disease diagnosis

N Petrellis - Symmetry, 2018 - mdpi.com
Image processing has been extensively used in various (human, animal, plant) disease
diagnosis approaches, assisting experts to select the right treatment. It has been applied to …

[PDF][PDF] Digital Mammogram Inferencing System Using Intuitionistic Fuzzy Theory.

S Mishra, M Prakash - Computer Systems Science & …, 2022 - cdn.techscience.cn
In the medical field, the detection of breast cancer may be a mysterious task. Physicians
must deduce a conclusion from a significantly vague knowledge base. A mammogram can …

Garment categorization using data mining techniques

S Jain, V Kumar - Symmetry, 2020 - mdpi.com
The apparel industry houses a huge amount and variety of data. At every step of the supply
chain, data is collected and stored by each supply chain actor. This data, when used …

Brain pathology identification using computer aided diagnostic tool: A systematic review

A Gudigar, U Raghavendra, A Hegde, M Kalyani… - Computer methods and …, 2020 - Elsevier
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-
of-life by reducing human errors in diagnosis. CAD can expedite decision-making on …

Hybrid feature extraction based brain tumor classification using an artificial neural network

KA Sathi, MS Islam - 2020 IEEE 5th International Conference …, 2020 - ieeexplore.ieee.org
The classification of brain tumor is a critical task to formulate a precise decision of the
physicians for providing an accurate treatment of the patient according to their classes …

Automated classification for brain MRIs based on 2D MF-DFA method

J Wang, W Shao, J Kim - Fractals, 2020 - World Scientific
Magnetic resonance image (MRI) is an important tool to diagnose human diseases
effectively. It is very important for research and clinical application to classify the normal and …

Neuroimaging computer‐aided diagnosis systems for Alzheimer's disease

V Karami, G Nittari, F Amenta - International Journal of Imaging …, 2019 - Wiley Online Library
This paper has reviewed the state‐of‐the‐art approaches for Computer Aided Diagnosis
Systems (CADS) for Alzheimer's Disease (AD) using neuroimaging. Identification of the …

Magnetic resonance imaging radiomics analysis for predicting hepatocellular carcinoma

NSM Haniff, MKBA Karim, NS Ali… - 2021 International …, 2021 - ieeexplore.ieee.org
Current technology allows for more accurate and precise diagnosis that able to classify the
tumour staging by quantifying the features extraction and medical images analysis. Hence …