Genitourinary melanoma: An overview for the clinician

DePalo, Danielle; Elleson, Kelly; Carr, Michael J.; Spiess, Philippe E.; Zager, Jonathan S.

doi:10.1016/j.ajur.2022.01.003

Cited by 8 publications

(14 citation statements)

References 137 publications

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“…Furthermore, when located in the distal segment or urethral meatus, the presence of a pigmented mass with potential ulceration and bleeding is the chief complaint. Amelanotic (achromic) melanomas, accounting for 10 %, present diagnostic challenges and may lead to potential confusion with benign conditions such as urethral ectropion or caruncles [ 2 , 6 , 7 ].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Primary metastatic melanoma of the female urethra: A case report and literature review

Bellouki,

El Aboudi,

Mikou

et al. 2024

International Journal of Surgery Case Reports

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Section: Discussionmentioning

confidence: 99%

“…Levine [ 7 ] introduced a staging system for urethral melanoma, delineated as follows: Stage A : Tumor confined to the submucosa. Stage B : Tumor infiltrating periurethral muscle in females and corpus spongiosum in males.…”

Section: Discussionmentioning

confidence: 99%

Primary metastatic melanoma of the female urethra: A case report and literature review

Bellouki,

El Aboudi,

Mikou

et al. 2024

International Journal of Surgery Case Reports

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“…It is ninth in position among the common cancer incidence in the world. It is the thirteenth for the cause of cancer-related death [7]. In China, the incidence and mortality of bladder cancer is first among the urinary system tumors, and with the advancement and changes in the lifestyle habits, the incidence and detection rate of bladder cancer has been increasing year by year [7,8].…”

Section: Concepts On Bladder Cancer and Epidemiology Characteristicsmentioning

confidence: 99%

The Recent Research Progress of CircRNA in Bladder Cancer

Liu¹,

Xu²

2023

ann urol oncol

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Bladder cancer is a major public health problem in the world, and is one of the most common malignant tumors in the genito-urinary system. Due to its high incidence and mortality, it remains a serious threat to human health. In recent years, related researches on the occurrence of bladder cancer found a certain connection between the expression level of circRNA and development of bladder cancer. circRNA can accomplish the purpose of promoting or inhibiting the occurrence and progression of bladder cancer by affecting the expression of related miRNA and mRNA. Higher expression levels of some circRNAs such as circITCH, circACVR2A, circPICALM, and circZKSCAN1 demonstrate an improved prognostic survival of patients with bladder cancer. Higher expression of circBPTF and circPRMT5 correlated with worse prognosis in bladder cancer patients. This article highlights a relationship between CircRNA and bladder cancer.

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“…To remove this noise, black-hat filtering and inpainting are needed. Black-hat filtering is a technique in morphological transformations [20], which can be written as (2), where is the results of black-hat filtering, is the original image filtered, is the filter used, and operator • is a closing operation where dilation and erosion occur.…”

Section: )mentioning

confidence: 99%

“…If it grows in a new place, spots or dots on the skin will grow. Melanoma can grow in all parts of the human body, including the head, neck, soles of the feet, and genitals [2]. The American Cancer Society [1] estimates that by 2021 in the United States, there will be approximately 106,110 new melanoma cases (62,260 cases in men and 43,850 cases in women).…”

Section: Introductionmentioning

confidence: 99%

Melanoma Detection using Convolutional Neural Network with Transfer Learning on Dermoscopic and Macroscopic Images

Millenia

Naufal²,

Siswantoro³

2022

J. Inf. Syst. Eng. Bus. Intell.

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Background: Melanoma is a skin cancer that starts when the melanocytes that produce the skin color pigment start to grow out of control and form a cancer. Detecting melanoma early before it spreads to the lymph nodes and other parts of the body is very important because it makes a big difference to the patient's 5-year life expectancy. Screening is the process of conducting a skin examination to suspect a mole is melanoma using dermoscopic or macroscopic images. However, manual screening takes a long time. Therefore, automatic melanoma detection is needed to speed up the melanoma detection process. The previous studies still have weakness because it has low precision or recall, which means the model cannot predict melanoma accurately. The distribution of melanoma and moles datasets is imbalanced where the number of melanomas is less than moles. In addition, in previous study, comparisons of several CNN transfer learning architectures have not been carried out on dermoscopic and macroscopic images. Objective: This study aims to detect melanoma using the Convolutional Neural Network (CNN) with transfer learning on dermoscopic and macroscopic melanoma images. CNN with Transfer learning is a popular method for classifying digital images with high accuracy. Methods: This study compares four CNN with transfer learning architectures, namely MobileNet, Xception, VGG16, and ResNet50 on dermoscopic and macroscopic image. This research also uses black-hat filtering and inpainting at the preprocessing stage to remove hair from the skin image. Results: MobileNet is the best model for classifying melanomas or moles in this experiment which has 83.86% of F1 score and 11 second of training time per epoch. Conclusion: MobileNet and Xception have high average F1 scores of 84.42% and 80.00%, so they can detect melanoma accurately even though the number of melanoma datasets is less than moles. Therefore, it can be concluded that MobileNet and Xception are suitable models for classifying melanomas and moles. However, MobileNet has the fastest training time per epoch which is 11 seconds. In the future, oversampling method can be implemented to balance the number of datasets to improve the performance of the classification model.

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Genitourinary melanoma: An overview for the clinician

Cited by 8 publications

References 137 publications

Primary metastatic melanoma of the female urethra: A case report and literature review

Primary metastatic melanoma of the female urethra: A case report and literature review

The Recent Research Progress of CircRNA in Bladder Cancer

Melanoma Detection using Convolutional Neural Network with Transfer Learning on Dermoscopic and Macroscopic Images

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