[HTML][HTML] A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions

T Islam, MS Hafiz, JR Jim, MM Kabir, MF Mridha - Healthcare Analytics, 2024‏ - Elsevier
Data augmentation involves artificially expanding a dataset by applying various
transformations to the existing data. Recent developments in deep learning have advanced …

Enhancing Brain Tumor Diagnosis: A Comparative Review of Systems with and without eXplainable AI

J Chathumina, K Jayakumar - 2024 5th Information …, 2024‏ - ieeexplore.ieee.org
Deep Learning (DL) and computer vision may be used to distinguish between various
anatomical features in the human body. As technology has developed, several DL methods …

Optimized brain tumor identification via graph sample and aggregate-attention network with Artificial Lizard Search Algorithm

C Moorthy, JC Sekhar, SI Khan, G Agrawal - Knowledge-Based Systems, 2024‏ - Elsevier
A brain tumour is an abnormal growth of brain nerves that interferes with normal brain
function. It causes a great deal of deaths. Timely detection and treatment are essential for …

ChatGPT-powered deep learning: elevating brain tumor detection in MRI scans

S Rawas, C Tafran, D AlSaeed - Applied Computing and Informatics, 2024‏ - emerald.com
Purpose Accurate diagnosis of brain tumors is crucial for effective treatment and improved
patient outcomes. Magnetic resonance imaging (MRI) is a common method for detecting …

EfficientNetV2 based for MRI brain tumor image classification

AA Waskita, JM Amda, DSK Sihono… - … on Computer, Control …, 2023‏ - ieeexplore.ieee.org
An accurate and timely diagnosis is of utmost importance when it comes to treating brain
tumors effectively. To facilitate this process, we have developed a brain tumor classification …

Deep Learning-Based Waste Classification with Transfer Learning Using EfficientNet-B0 Model

R Risfendra, GF Ananda, H Setyawan - Jurnal RESTI (Rekayasa …, 2024‏ - jurnal.iaii.or.id
Recycling of waste is a significant challenge in modern waste management. Conventional
techniques that use inductive and capacitive proximity sensors exhibit limitations in accuracy …

A Comparative Analysis on Machine Learning based Brain Tumor Detection Techniques

H Negi, A Bhatt, S Dimri, B Kumar - 2023 7th International …, 2023‏ - ieeexplore.ieee.org
It has been observed that finding an anomaly, like a fracture in a bone or unwanted growth
in an organ of human being, has been easier since the advent of advanced technologies …

EfficientNet-B7 framework for anomaly detection in mammogram images

S HS, K Sooda, B Karunakara Rai - Multimedia Tools and Applications, 2024‏ - Springer
At present, handling imbalanced data, deciphering complex data patterns, selecting suitable
unsupervised learning algorithms, and ensuring computational efficiency are among the …

Regression modeling with convolutional neural network for predicting extent of resection from preoperative MRI in giant pituitary adenomas: a pilot study

BK Patel, L Tariciotti, L DiRocco, A Mandile… - Journal of …, 2025‏ - thejns.org
OBJECTIVE Giant pituitary adenomas (GPAs) are challenging skull base tumors due to their
size and proximity to critical neurovascular structures. Achieving gross-total resection (GTR) …