[PDF][PDF] An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding.
Image segmentation is a challenging process in numerous applications. Region growing is
one of the segmentation techniques as a basis for the Seeded Region Growing method. A …
one of the segmentation techniques as a basis for the Seeded Region Growing method. A …
Cross-modality guided contrast enhancement for improved liver tumor image segmentation
Tumor segmentation in Computed Tomography (CT) images is a crucial step in image-
guided surgery. However, low-contrast CT images impede the performance of subsequent …
guided surgery. However, low-contrast CT images impede the performance of subsequent …
GPU acceleration of liver enhancement for tumor segmentation
Background and objective: Medical image segmentation plays a vital role in medical image
analysis. There are many algorithms developed for medical image segmentation which are …
analysis. There are many algorithms developed for medical image segmentation which are …
The local ternary pattern encoder–decoder neural network for dental image segmentation
Recent advances in medical imaging analyses, especially the use of deep learning, are
helping to identify, detect, classify, and quantify patterns in radiographs. At the centre of …
helping to identify, detect, classify, and quantify patterns in radiographs. At the centre of …
Fast parallel vessel segmentation
Abstract Background and Objective: Accurate and fast vessel segmentation from liver slices
remain challenging and important tasks for clinicians. The algorithms from the literature are …
remain challenging and important tasks for clinicians. The algorithms from the literature are …
Automatically density based breast segmentation for mammograms by using dynamic K-means algorithm and seed based region growing
A Elmoufidi, K El Fahssi… - 2015 IEEE …, 2015 - ieeexplore.ieee.org
This paper presents a method for segment and detects the boundary of different breast
tissue regions in mammograms by using dynamic K-means clustering algorithm and Seed …
tissue regions in mammograms by using dynamic K-means clustering algorithm and Seed …
Colorization and automated segmentation of human T2 MR brain images for characterization of soft tissues
Characterization of tissues like brain by using magnetic resonance (MR) images and
colorization of the gray scale image has been reported in the literature, along with the …
colorization of the gray scale image has been reported in the literature, along with the …
Automated flower species detection and recognition from digital images
AA Albadarneh - 2016 - search.proquest.com
Automated Flower Species Detection and Recognition from Digital Images Page 1
Automated Flower Species Detection and Recognition from Digital Images By Aalaa …
Automated Flower Species Detection and Recognition from Digital Images By Aalaa …
Object extraction from T2 weighted brain MR image using histogram based gradient calculation
Several segmentation methods have been reported with their own pros and cons. Here we
proposed a method for object extraction from T2 weighted (T2) brain magnetic resonance …
proposed a method for object extraction from T2 weighted (T2) brain magnetic resonance …
Improved Random Forest for the Automatic Identification of Spodoptera frugiperda Larval Instar Stages
Spodoptera frugiperda (fall armyworm, FAW) is a global agriculture pest. Adults have a
strong migratory ability and larvae feed on the host stalks, which pose a serious threat for …
strong migratory ability and larvae feed on the host stalks, which pose a serious threat for …