Deep transfer learning approaches in performance analysis of brain tumor classification using MRI images

C Srinivas, NP KS, M Zakariah… - Journal of …, 2022 - Wiley Online Library
Brain tumor classification is a very important and the most prominent step for assessing life‐
threatening abnormal tissues and providing an efficient treatment in patient recovery. To …

Customized VGG19 architecture for pneumonia detection in chest X-rays

N Dey, YD Zhang, V Rajinikanth, R Pugalenthi… - Pattern Recognition …, 2021 - Elsevier
Pneumonia is one of the major illnesses in children and aged humans due to the Infection in
the lungs. Early analysis of pneumonia is necessary to prepare for a possible treatment …

Classification and analysis of pistachio species with pre-trained deep learning models

D Singh, YS Taspinar, R Kursun, I Cinar, M Koklu… - Electronics, 2022 - mdpi.com
Pistachio is a shelled fruit from the anacardiaceae family. The homeland of pistachio is the
Middle East. The Kirmizi pistachios and Siirt pistachios are the major types grown and …

VGG19 network assisted joint segmentation and classification of lung nodules in CT images

MA Khan, V Rajinikanth, SC Satapathy, D Taniar… - Diagnostics, 2021 - mdpi.com
Pulmonary nodule is one of the lung diseases and its early diagnosis and treatment are
essential to cure the patient. This paper introduces a deep learning framework to support the …

Weighted average ensemble deep learning model for stratification of brain tumor in MRI images

V Anand, S Gupta, D Gupta, Y Gulzar, Q Xin, S Juneja… - Diagnostics, 2023 - mdpi.com
Brain tumor diagnosis at an early stage can improve the chances of successful treatment
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …

Automated brain tumor identification using magnetic resonance imaging: A systematic review and meta-analysis

O Kouli, A Hassane, D Badran, T Kouli… - Neuro-oncology …, 2022 - academic.oup.com
Background Automated brain tumor identification facilitates diagnosis and treatment
planning. We evaluate the performance of traditional machine learning (TML) and deep …

Deep Learning-powered biomedical photoacoustic imaging

X Wei, T Feng, Q Huang, Q Chen, C Zuo, H Ma - Neurocomputing, 2023 - Elsevier
Photoacoustic Imaging (PAI) is an emerging hybrid imaging modality that combines optical
imaging and ultrasound imaging, offering advantages such as high resolution, strong …

3D shearlet-based descriptors combined with deep features for the classification of Alzheimer's disease based on MRI data

S Alinsaif, J Lang… - Computers in Biology …, 2021 - Elsevier
Alzheimer's disease (AD) is a neurodegenerative disease that afflicts millions of people
worldwide. Early detection of AD is critical, as drug trials show a promising advantage to …

Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features

A Malekzadeh, A Zare, M Yaghoobi, HR Kobravi… - Sensors, 2021 - mdpi.com
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …

Automated segmentation of leukocyte from hematological images—a study using various CNN schemes

S Kadry, V Rajinikanth, D Taniar… - The Journal of …, 2022 - Springer
Medical images play a fundamental role in disease screening, and automated evaluation of
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …