Comparative approach of MRI-based brain tumor segmentation and classification using genetic algorithm
The detection of a brain tumor and its classification from modern imaging modalities is a
primary concern, but a time-consuming and tedious work was performed by radiologists or …
primary concern, but a time-consuming and tedious work was performed by radiologists or …
[Retracted] Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques
M Arif, F Ajesh, S Shamsudheen… - Journal of …, 2022 - Wiley Online Library
Radiology is a broad subject that needs more knowledge and understanding of medical
science to identify tumors accurately. The need for a tumor detection program, thus …
science to identify tumors accurately. The need for a tumor detection program, thus …
Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM
The segmentation, detection, and extraction of infected tumor area from magnetic resonance
(MR) images are a primary concern but a tedious and time taking task performed by …
(MR) images are a primary concern but a tedious and time taking task performed by …
Deep convolutional models improve predictions of macaque V1 responses to natural images
Despite great efforts over several decades, our best models of primary visual cortex (V1) still
predict spiking activity quite poorly when probed with natural stimuli, highlighting our limited …
predict spiking activity quite poorly when probed with natural stimuli, highlighting our limited …
Hierarchical temporal prediction captures motion processing along the visual pathway
Visual neurons respond selectively to features that become increasingly complex from the
eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) …
eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) …
Neural system identification for large populations separating “what” and “where”
Neuroscientists classify neurons into different types that perform similar computations at
different locations in the visual field. Traditional methods for neural system identification do …
different locations in the visual field. Traditional methods for neural system identification do …
Learning divisive normalization in primary visual cortex
Divisive normalization (DN) is a prominent computational building block in the brain that has
been proposed as a canonical cortical operation. Numerous experimental studies have …
been proposed as a canonical cortical operation. Numerous experimental studies have …
Explanatory models in neuroscience, Part 1: Taking mechanistic abstraction seriously
Despite the recent success of neural network models in mimicking animal performance on
various tasks, critics worry that these models fail to illuminate brain function. We take it that a …
various tasks, critics worry that these models fail to illuminate brain function. We take it that a …
Neural representation of natural images in visual area V2
BDB Willmore, RJ Prenger, JL Gallant - Journal of Neuroscience, 2010 - Soc Neuroscience
Area V2 is a major visual processing stage in mammalian visual cortex, but little is currently
known about how V2 encodes information during natural vision. To determine how V2 …
known about how V2 encodes information during natural vision. To determine how V2 …
Model constrained by visual hierarchy improves prediction of neural responses to natural scenes
Accurate estimation of neuronal receptive fields is essential for understanding sensory
processing in the early visual system. Yet a full characterization of receptive fields is still …
processing in the early visual system. Yet a full characterization of receptive fields is still …