中文
相关论文

相关论文: Multiple EffNet/ResNet Architectures for Melanoma …

200 篇论文

Cancer is a leading cause of death worldwide, necessitating advancements in early detection and treatment technologies. In this paper, we present a novel and highly efficient melanoma detection framework that synergistically combines the…

图像与视频处理 · 电气工程与系统科学 2024-08-05 Peng Zhang , Divya Chaudhary

Skin cancer is the most common type of cancer. Specifically, melanoma is the cause of 75% of skin cancer deaths, although it is the least common skin cancer. Better detection of melanoma could have a positive impact on millions of people.…

计算机视觉与模式识别 · 计算机科学 2023-02-21 Chengdong Yao

Skin cancer is the most common cancer in the existing world constituting one-third of the cancer cases. Benign skin cancers are not fatal, can be cured with proper medication. But it is not the same as the malignant skin cancers. In the…

图像与视频处理 · 电气工程与系统科学 2022-12-21 Dusa Sai Charan , Hemanth Nadipineni , Subin Sahayam , Umarani Jayaraman

Melanoma is a type of skin cancer with the most rapidly increasing incidence. Early detection of melanoma using dermoscopy images significantly increases patients' survival rate. However, accurately classifying skin lesions by eye,…

计算机视觉与模式识别 · 计算机科学 2019-02-14 Xiaoxiao Li , Junyan Wu , Eric Z. Chen , Hongda Jiang

Today, skin cancer is considered as one of the most dangerous and common cancers in the world which demands special attention. Skin cancer may be developed in different types; including melanoma, actinic keratosis, basal cell carcinoma,…

计算机视觉与模式识别 · 计算机科学 2024-04-02 Amir Faghihi , Mohammadreza Fathollahi , Roozbeh Rajabi

Melanoma is a type of skin cancer developed from melanocytes. It is one of the most lethal types of cancer, accounting for approximately 75% of skin cancer deaths. Late stage melanoma is very difficult to treat, since the cancer cells are…

定量方法 · 定量生物学 2018-11-28 Xue Teng , Fuad Gwadry , Haley McConkey , Scott Ernst , Femida Gwadry-Sridhar

Melanoma is the deadliest form of skin cancer. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced.…

Automated skin lesion classification using deep learning has shown remarkable accuracy, yet clinical adoption remains limited due to the "black box" nature of these models. We present MelanomaNet, an explainable deep learning system for…

计算机视觉与模式识别 · 计算机科学 2025-12-11 Sukhrobbek Ilyosbekov

Among the different types of skin cancer, melanoma is considered to be the deadliest and is difficult to treat at advanced stages. Detection of melanoma at earlier stages can lead to reduced mortality rates. Desktop-based computer-aided…

图像与视频处理 · 电气工程与系统科学 2022-05-26 Upender Kalwa , Christopher Legner , Taejoon Kong , Santosh Pandey

Cancerous skin lesions are one of the most common malignancies detected in humans, and if not detected at an early stage, they can lead to death. Therefore, it is crucial to have access to accurate results early on to optimize the chances…

图像与视频处理 · 电气工程与系统科学 2023-05-19 Daniel Alonso Villanueva Nunez , Yongmin Li

We present our winning solution to the SIIM-ISIC Melanoma Classification Challenge. It is an ensemble of convolutions neural network (CNN) models with different backbones and input sizes, most of which are image-only models while a few of…

计算机视觉与模式识别 · 计算机科学 2020-10-13 Qishen Ha , Bo Liu , Fuxu Liu

Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence (AI) has proven to be helpful for enhancing melanoma…

Malignant melanoma is the deadliest form of skin cancer and, in recent years, is rapidly growing in terms of the incidence worldwide rate. The most effective approach to targeted treatment is early diagnosis. Deep learning algorithms,…

图像与视频处理 · 电气工程与系统科学 2020-09-21 Mario Manzo , Simone Pellino

Accurate and efficient classification of different types of cancer is critical for early detection and effective treatment. In this paper, we present the results of our experiments using the EfficientNet algorithm for classification of…

图像与视频处理 · 电气工程与系统科学 2023-07-14 Romario Sameh Samir

This work seeks to determine how modern machine learning techniques may be applied to the previously unexplored topic of melanoma diagnostics using digital pathology. We curated a new dataset of 50 patient cases of cutaneous melanoma using…

计算机视觉与模式识别 · 计算机科学 2018-06-14 Adon Phillips , Iris Teo , Jochen Lang

This study focuses on automatic skin cancer detection using a Meta-learning approach for dermoscopic images. The aim of this study is to explore the benefits of the generalization of the knowledge extracted from non-medical data in the…

计算机视觉与模式识别 · 计算机科学 2021-04-23 Sara I. Garcia

The rapid advancement of deep learning in medical image analysis has greatly enhanced the accuracy of skin cancer classification. However, current state-of-the-art models, especially those based on transfer learning like ResNet50, come with…

图像与视频处理 · 电气工程与系统科学 2025-05-29 Abdullah Al Mamun , Pollob Chandra Ray , Md Rahat Ul Nasib , Akash Das , Jia Uddin , Md Nurul Absur

Melanoma is one of the most serious skin cancers that can occur in any part of the human skin. Early diagnosis of melanoma lesions will significantly increase their chances of being cured. Improving melanoma segmentation will help doctors…

图像与视频处理 · 电气工程与系统科学 2023-01-12 Mohamad Taghizadeh , Karim Mohammadi

Melanoma is a life-threatening form of skin cancer when left undiagnosed at the early stages. Although there are more cases of non-melanoma cancer than melanoma cancer, melanoma cancer is more deadly. Early detection of melanoma is crucial…

图像与视频处理 · 电气工程与系统科学 2020-05-15 Shreshth Saini , Divij Gupta , Anil Kumar Tiwari

Melanoma is one of the ten most common cancers in the US. Early detection is crucial for survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the potential to improve cancer detection rates, but its…

计算机视觉与模式识别 · 计算机科学 2019-05-16 Devansh Bisla , Anna Choromanska , Jennifer A. Stein , David Polsky , Russell Berman