Advances in Optimal Detection of Cancer by Image Processing; Experience with Lung and Breast Cancers

Mohammadzadeh, Zeinab; Safdari, Reza; Ghazisaeidi, Marjan; Davoodi, Somayeh; Azadmanjir, Zahra

doi:10.7314/apjcp.2015.16.14.5613

Cited by 20 publications

(9 citation statements)

References 43 publications

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“…Image processing techniques have shown success in improving cancer diagnosis through several mechanisms. Recent advances have been made into classifying histopathological images of malignancies (Mohammadzadeh et al 2015); machine learning algorithms have shown to be promising tools (Benzheng Wei et al 2017;Komura and Ishikawa 2018;Dimitriou et al 2019;Iizuka et al 2020). Apart from microscopy, other sources of images have also yielded possible means for diagnosing several types of cancers, i.e.…”

Section: Introductionmentioning

confidence: 99%

Fractal dimension analysis as an easy computational approach to improve breast cancer histopathological diagnosis

Silva¹,

Monteiro²,

Moreira

et al. 2021

Appl. Microsc.

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Histopathology is a well-established standard diagnosis employed for the majority of malignancies, including breast cancer. Nevertheless, despite training and standardization, it is considered operator-dependent and errors are still a concern. Fractal dimension analysis is a computational image processing technique that allows assessing the degree of complexity in patterns. We aimed here at providing a robust and easily attainable method for introducing computer-assisted techniques to histopathology laboratories. Slides from two databases were used: A) Breast Cancer Histopathological; and B) Grand Challenge on Breast Cancer Histology. Set A contained 2480 images from 24 patients with benign alterations, and 5429 images from 58 patients with breast cancer. Set B comprised 100 images of each type: normal tissue, benign alterations, in situ carcinoma, and invasive carcinoma. All images were analyzed with the FracLac algorithm in the ImageJ computational environment to yield the box count fractal dimension (Db) results. Images on set A on 40x magnification were statistically different (p = 0.0003), whereas images on 400x did not present differences in their means. On set B, the mean Db values presented promissing statistical differences when comparing. Normal and/or benign images to in situ and/or invasive carcinoma (all p < 0.0001). Interestingly, there was no difference when comparing normal tissue to benign alterations. These data corroborate with previous work in which fractal analysis allowed differentiating malignancies. Computer-aided diagnosis algorithms may beneficiate from using Db data; specific Db cut-off values may yield ~ 99% specificity in diagnosing breast cancer. Furthermore, the fact that it allows assessing tissue complexity, this tool may be used to understand the progression of the histological alterations in cancer.

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Section: Introductionmentioning

confidence: 99%

Fractal dimension analysis as an easy computational approach to improve breast cancer histopathological diagnosis

Silva¹,

Monteiro²,

Moreira

et al. 2021

Appl. Microsc.

View full text Add to dashboard Cite

show abstract

“…Cancer is a major cause of death in the world with high health priority and has become an important issue in public health. [1][2][3] According to GLOBOCAN 2012 estimations, there were about 14.1 million new cancer cases, 8.2 million cancer deaths and 32.6 million people who living with cancer (within 5 years of diagnosis) in 2012 worldwide. 4 Occupational cancer is occurred due to exposure to many environmental and occupational factors including biological, chemical and physical carcinogens.…”

Section: Introductionmentioning

confidence: 99%

Occupational cancers management, via telehealth opportunities

Mohammadzadeh

Davoodi

2018

Int J Sci Rep

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<p class="abstract">Because of the importance and huge burden of occupational cancers for the population today, health policy makers should look for innovative and cost effective ways to manage these diseases. Information technology bases such as telehealth have prominent impacts in many areas of medicine. Telehealth approaches including teleoncology and teleoccupational therapy are the solutions that help to provide quick access to high quality services for cancer patients in remote areas. The most important impact of telehealth methods is enhancing care cost-effectiveness and eliminating the disparities in access to cancer care for cancer patient. For the reasons mentioned it is necessary to use telehealth in occupational cancer care same as other fields of cancer. In this paper application of telehealth opportunities in occupational cancers have been described.</p>

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“…Cancer is not only a personal disease and beside its great influences on many aspects of patient life (Abbasnezhad et al, 2015); it has socioeconomically impacts (Cannon et al, 2012). Raise individual awareness about cancer leads to prevention and early detection of cancer and reduce mentioned costs (Mohammadzadeh et al, 2015). Patients with cancer desire to obtain updated information about different aspects of their disease such as sign and symptoms, diagnosis, treatment, side effects of various methods of treatment, follow up and cancer effect on their life (Shahrokni et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Online Social Networks - Opportunities for Empowering Cancer Patients

Mohammadzadeh

Davoodi²,

Ghazisaeidi³

2016

Asian Pacific Journal of Cancer Prevention

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Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

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Advances in Optimal Detection of Cancer by Image Processing; Experience with Lung and Breast Cancers

Cited by 20 publications

References 43 publications

Fractal dimension analysis as an easy computational approach to improve breast cancer histopathological diagnosis

Fractal dimension analysis as an easy computational approach to improve breast cancer histopathological diagnosis

Occupational cancers management, via telehealth opportunities

Online Social Networks - Opportunities for Empowering Cancer Patients

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