HighlightsLeydig cell tumor is a testicular tumor with a low incidence accounting for 1–3% of testicular neoplasms.Only about 10% of them show malignant behavior in the form of metastatic disease.When diagnosed and treated early, long-term favorable outcomes are seen even with its potential metastatic behavior.

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Using the time-independent Schrödinger equation with a velocity-dependent potential the energy dependence of the corresponding scattering phase shifts, when the energy is changed by a small amount E from an arbitrary unperturbed value E 0 , is studied. We expand k cot δ as a power series in E and obtain analytic formulas for the effective range expansion parameters to all orders in the perturbing energy. Formulas for the corresponding wave function changes are also developed. At low energies the Bethe formula for the effective range is reproduced and an expression for the shape-dependent term is obtained. The derived formalism is relevant to fields like nuclear and atomic physics. Examples that demonstrate the effectiveness of the derived formalism are presented.

Recent years have witnessed a huge revolution in developing automated diagnosis for different diseases such as cancer using medical image processing. Many researchers have been conducted in this field. Analyzing medical microscopic images provide pathology medical track with large information about the status of the patients and the progress of the diseases and help in detecting any pathological changes in tissues. Automation of the diagnosis of these images will lead to a better, faster and enhanced diagnosis for different hematological and histological images. This paper proposes an automated approach for analyzing blood smear microscopic images to help in diagnosing anemia using quantitative analysis of red blood cells in intestine villi tissue. The diagnoses depends on counting the number of blue and red stained blood cells that contain iron in each villi separately, then, it calculates the percentage of blue cells and red cells in the experimented image. The experimental results have shown that using digital image processing techniques through processing the image into different stages as including noise removal, image sharpening, enhancing contrast, find region of interest, isolating color, removing edges, and counting cells leads to a successful outcome and the diagnose of anemia.