Papers Cancer Classification
“Cancer Classification” 태그가 달린 논문 260편 · 필터 해제
Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers
Technology aided platforms provide reliable tools in almost every field these days. These tools being supported by computational power are significant for applications that need sensitive and precise data analysis. One s…
Cancer ClassificationGeneral ClassificationLesion DetectionLesion Segmentation+1Joint 2D-3D Breast Cancer Classification
Breast cancer is the malignant tumor that causes the highest number of cancer deaths in females. Digital mammograms (DM or 2D mammogram) and digital breast tomosynthesis (DBT or 3D mammogram) are the two types of mammogr…
Breast Cancer DetectionCancer ClassificationClassificationGeneral ClassificationIntegration of Convolutional Neural Networks for Pulmonary Nodule Malignancy Assessment in a Lung Cancer Classification Pipeline
The early identification of malignant pulmonary nodules is critical for better lung cancer prognosis and less invasive chemo or radio therapies. Nodule malignancy assessment done by radiologists is extremely useful for p…
Cancer ClassificationGeneral ClassificationPrognosisTransfer LearningInception Architecture and Residual Connections in Classification of Breast Cancer Histology Images
This paper presents results of applying Inception v4 deep convolutional neural network to ICIAR-2018 Breast Cancer Classification Grand Challenge, part a. The Challenge task is to classify breast cancer biopsy results, p…
Binary ClassificationCancer ClassificationClassificationClassification Of Breast Cancer Histology Images+2Sparse High-Dimensional Isotonic Regression
We consider the problem of estimating an unknown coordinate-wise monotone function given noisy measurements, known as the isotonic regression problem. Often, only a small subset of the features affects the output. This m…
Cancer ClassificationregressionVocal Bursts Intensity PredictionEstimating Skin Tone and Effects on Classification Performance in Dermatology Datasets
Recent advances in computer vision and deep learning have led to breakthroughs in the development of automated skin image analysis. In particular, skin cancer classification models have achieved performance higher than t…
BIG-bench Machine LearningCancer ClassificationGeneral ClassificationSkin Cancer ClassificationData Augmentation for Skin Lesion using Self-Attention based Progressive Generative Adversarial Network
Deep Neural Networks (DNNs) show a significant impact on medical imaging. One significant problem with adopting DNNs for skin cancer classification is that the class frequencies in the existing datasets are imbalanced. T…
Cancer ClassificationData AugmentationGeneral ClassificationGenerative Adversarial Network+1A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
Oral cancer incidence is rapidly increasing worldwide. The most important determinant factor in cancer survival is early diagnosis. To facilitate large scale screening, we propose a fully automated pipeline for oral canc…
Cancer ClassificationClassificationGeneral ClassificationOral Cancer Classification+2A CNN toolbox for skin cancer classification
We describe a software toolbox for the configuration of deep neural networks in the domain of skin cancer classification. The implemented software architecture allows developers to quickly set up new convolutional neural…
AutoMLCancer ClassificationClassificationGeneral Classification+2Deep neural network or dermatologist?
Deep learning techniques have proven high accuracy for identifying melanoma in digitised dermoscopic images. A strength is that these methods are not constrained by features that are pre-defined by human semantics. A dow…
Cancer ClassificationDiagnosticSkin Cancer ClassificationIntegrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
Different aspects of a clinical sample can be revealed by multiple types of omics data. Integrated analysis of multi-omics data provides a comprehensive view of patients, which has the potential to facilitate more accura…
Cancer ClassificationClassificationDecision MakingGeneral Classification+2Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images
Digital histology images are amenable to the application of convolutional neural network (CNN) for analysis due to the sheer size of pixel data present in them. CNNs are generally used for representation learning from sm…
Cancer ClassificationRepresentation LearningSkin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet
Skin cancer, a major form of cancer, is a critical public health problem with 123,000 newly diagnosed melanoma cases and between 2 and 3 million non-melanoma cases worldwide each year. The leading cause of skin cancer is…
Cancer ClassificationDecision MakingDiagnosticGeneral Classification+2Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images
Purpose: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in-vivo imaging with confocal la…
Cancer ClassificationGeneral Classificationimage-classificationImage Classification+1Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification
Large amounts of unlabelled data are commonplace for many applications in computational pathology, whereas labelled data is often expensive, both in time and cost, to acquire. We investigate the performance of unsupervis…
Cancer ClassificationClusteringGeneral ClassificationSkin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks
In the last few years, Deep Learning (DL) has been showing superior performance in different modalities of biomedical image analysis. Several DL architectures have been proposed for classification, segmentation, and dete…
Cancer ClassificationClassificationGeneral ClassificationImage Segmentation+4Breast Cancer Classification with Ultrasound Images Based on SLIC
Ultrasound image diagnosis of breast tumors has been widely used in recent years. However, there are some problems of it, for instance, poor quality, intense noise and uneven echo distribution, which has created a huge o…
Cancer ClassificationClassificationClusteringGeneral ClassificationHistopathologic Image Processing: A Review
Histopathologic Images (HI) are the gold standard for evaluation of some tumors. However, the analysis of such images is challenging even for experienced pathologists, resulting in problems of inter and intra observer. B…
Cancer ClassificationStatistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms
Objective: A colon microarray data is a repository of thousands of gene expressions with different strengths for each cancer cell. It is necessary to detect which genes are responsible for cancer growth. This study pre…
BIG-bench Machine LearningCancer ClassificationGeneral ClassificationLook, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification
One issue with computer based histopathology image analysis is that the size of the raw image is usually very large. Taking the raw image as input to the deep learning model would be computationally expensive while resiz…
Cancer ClassificationGeneral Classification