Related papers: Skin Cancer Images Classification using Transfer L…

This study evaluates the effectiveness of deep learning models in classifying histopathological images for early and accurate detection of breast cancer. Eight advanced models, including ResNet-50, DenseNet-121, ResNeXt-50, Vision…

Skin cancer is a treatable disease if discovered early. We provide a production-specific solution to the skin cancer classification problem that matches human performance in melanoma identification by training a vision transformer on…

Skin cancer is one of the most common types of cancer around the world. For this reason, over the past years, different approaches have been proposed to assist detect it. Nonetheless, most of them are based only on dermoscopy images and do…

Accurate classification of Acute Lymphoblastic Leukemia (ALL) from peripheral blood smear images is essential for early diagnosis and effective treatment planning. This study investigates the use of transfer learning with pretrained…

Skin diseases are among the most prevalent health concerns worldwide, yet conventional diagnostic methods are often costly, complex, and unavailable in low-resource settings. Automated classification using deep learning has emerged as a…

Breast cancer is one of the most threatening diseases in women's life; thus, the early and accurate diagnosis plays a key role in reducing the risk of death in a patient's life. Mammography stands as the reference technique for breast…

Skin cancer is one of the most prevalent forms of human cancer. It is recognized mainly visually, beginning with clinical screening and continuing with the dermoscopic examination, histological assessment, and specimen collection. Deep…

According to PBS, nearly one-third of Americans lack access to primary care services, and another forty percent delay going to avoid medical costs. As a result, many diseases are left undiagnosed and untreated, even if the disease shows…

Computer-aided diagnosis (CAD) based on histopathological imaging has progressed rapidly in recent years with the rise of machine learning based methodologies. Traditional approaches consist of training a classification model using features…

This work proposes a classification approach for breast cancer histopathologic images (HI) that uses transfer learning to extract features from HI using an Inception-v3 CNN pre-trained with ImageNet dataset. We also use transfer learning on…

Lung cancer, a malignancy originating in lung tissues, is commonly diagnosed and classified using medical imaging techniques, particularly computed tomography (CT). Despite the integration of machine learning and deep learning methods, the…

Melanoma is regarded as the most threatening among all skin cancers. There is a pressing need to build systems which can aid in the early detection of melanoma and enable timely treatment to patients. Recent methods are geared towards…

The past years have seen a considerable increase in cancer cases. However, a cancer diagnosis is often complex and depends on the types of images provided for analysis. It requires highly skilled practitioners but is often time-consuming…

Melanoma is a curable aggressive skin cancer if detected early. Typically, the diagnosis involves initial screening with subsequent biopsy and histopathological examination if necessary. Computer aided diagnosis offers an objective score…

The use of Convolutional Neural Networks (CNNs) has greatly improved the interpretation of medical images. However, conventional CNNs typically demand extensive computational resources and large training datasets. To address these…

Deep learning is the current bet for image classification. Its greed for huge amounts of annotated data limits its usage in medical imaging context. In this scenario transfer learning appears as a prominent solution. In this report we aim…

The brain tumor is the most aggressive kind of tumor and can cause low life expectancy if diagnosed at the later stages. Manual identification of brain tumors is tedious and prone to errors. Misdiagnosis can lead to false treatment and thus…

Skin cancer is a major concern to public health, accounting for one-third of the reported cancers. If not detected early, the cancer has the potential for severe consequences. Recognizing the critical need for effective skin cancer…

Prostate cancer is the most dangerous cancer diagnosed in men worldwide. Prostate diagnosis has been affected by many factors, such as lesion complexity, observer visibility, and variability. Many techniques based on Magnetic Resonance…

Skin cancer (SC) stands out as one of the most life-threatening forms of cancer, with its danger amplified if not diagnosed and treated promptly. Early intervention is critical, as it allows for more effective treatment approaches. In…