A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images
This paper presents a new algorithm for automatic detection of regions of interest in whole
slide histopathological images. The proposed algorithm generates and classifies …
slide histopathological images. The proposed algorithm generates and classifies …
Tumor localization in tissue microarrays using rotation invariant superpixel pyramids
Tumor localization is an important component of histopathology image analysis; it has yet to
be reliably automated for breast cancer histopathology. This paper investigates the use of …
be reliably automated for breast cancer histopathology. This paper investigates the use of …
Fast regions-of-interest detection in whole slide histopathology images
In this paper, we present a novel superpixel based Region of Interest (ROI) search and
segmentation algorithm. The proposed superpixel generation method differs from pioneer …
segmentation algorithm. The proposed superpixel generation method differs from pioneer …
Multilevel multiobjective particle swarm optimization guided superpixel algorithm for histopathology image detection and segmentation
A Kanadath, J Angel Arul Jothi, S Urolagin - Journal of Imaging, 2023 - mdpi.com
Histopathology image analysis is considered as a gold standard for the early diagnosis of
serious diseases such as cancer. The advancements in the field of computer-aided …
serious diseases such as cancer. The advancements in the field of computer-aided …
Dsnet: A dual-stream framework for weakly-supervised gigapixel pathology image analysis
We present a novel weakly-supervised framework for classifying whole slide images (WSIs).
WSIs, due to their gigapixel resolution, are commonly processed by patch-wise classification …
WSIs, due to their gigapixel resolution, are commonly processed by patch-wise classification …
Automated detection of DCIS in whole-slide H&E stained breast histopathology images
This paper presents and evaluates a fully automatic method for detection of ductal
carcinoma in situ (DCIS) in digitized hematoxylin and eosin (H&E) stained histopathological …
carcinoma in situ (DCIS) in digitized hematoxylin and eosin (H&E) stained histopathological …
A hybrid method of superpixel segmentation algorithm and deep learning method in histopathological image segmentation
A Albayrak, G Bilgin - 2018 Innovations in Intelligent Systems …, 2018 - ieeexplore.ieee.org
Manual analysis of cell morphology in high resolutional histopathological images is a
tedious and time consuming task for pathologists. In recent years, computer assisted …
tedious and time consuming task for pathologists. In recent years, computer assisted …
Machine learning based classification of colorectal cancer tumour tissue in whole-slide images
The recent introduction of whole-slide scanning systems enabled accumulation of high-
quality pathology images into large collections, thus opening new perspectives in cancer …
quality pathology images into large collections, thus opening new perspectives in cancer …
A novel texture descriptor for detection of glandular structures in colon histology images
K Sirinukunwattana, DRJ Snead… - Medical Imaging 2015 …, 2015 - spiedigitallibrary.org
The first step prior to most analyses on most histopathology images is the detection of area
of interest. In this work, we present a superpixel-based approach for glandular structure …
of interest. In this work, we present a superpixel-based approach for glandular structure …
Histopathology breast cancer detection and classification using optimized superpixel clustering algorithm and support vector machine
R Saturi, P Chand Parvataneni - Journal of The Institution of Engineers …, 2022 - Springer
In recent decades, nuclei cell classification in histology has played a significant role in early
diagnosis of breast cancer. However, it is a challenging task, due to the presence of small …
diagnosis of breast cancer. However, it is a challenging task, due to the presence of small …