Adapting CASA for the Gynecological Department  of EHU-Oran

Adaptation de CASA au service de gynécologie de l'EHU-Oran

Chahinaize Zaoui, Diya El-Hak Boucherit, Keltouma Tadj, Ibrahim Ouslim, Moulai Driss Cherif Remal, Wassila Mohand Arab, Ouslim Mohamed, Boucherit El Hassen Sahraoui Tewfik

Chahinaize Zaoui, Diya El-Hak Boucherit, Keltouma Tadj, Ibrahim Ouslim, Moulai Driss Cherif Remal, Wassila Mohand Arab, Ouslim Mohamed, Boucherit El Hassen Sahraoui Tewfik, « Adapting CASA for the Gynecological Department  of EHU-Oran  », Aleph [],  | 2024, 27 March 2024, 22 May 2024. URL : https://aleph.edinum.org/11285

It is estimated that there are 48.5 million couples suffering from infertility worldwide, where 20-30% of cases are of male origin, and the market is expected to collapse. The global cost of male infertility is estimated at $301.5 million. Computer-aided semen analysis (CASA) is a term that refers to automatic or semi-automatic semen analysis techniques. Automated analysis of the ejaculate using equipment using imaging technology. CASA Systems have been developed to assist these experts in measurement. Closed (hidden) commercial systems need to develop their own system to understand the system. How to get the job done: developing static and dynamic image processing algorithms on a high-performance hardware platform. The basic idea is the same principle but takes advantage of technological advancement in the computer and electronic fields. Our main objective of this work was to conduct an investigation on automatic semen analysis in order to propose a method for designing a sperm processing (EL-MED CASA ZRO) system using image processing techniques implemented on an embedded system. We proposed the use of the PC on board, the Raspberry Pi, as a portable and very economical hardware platform for processing, with access to the Cloud for intensive computing if needed. For this reason, we plan to implement this in the very near future and publish later, but for now, we will classify this approach as a perspective.

On estime qu’il y a 48,5 millions de couples souffrant d’infertilité dans le monde, où 20 à 30% des cas sont d’origine masculine, et le marché devrait s’effondrer. Le coût mondial de l’infertilité masculine est estimé à 301,5 millions de dollars. L’analyse de sperme assistée par ordinateur (CASA) est un terme qui fait référence aux techniques d’analyse de sperme automatique ou semi-automatique. L'analyse automatisée de l’éjaculat à l’aide d’un équipement utilisant la technologie d’imagerie. Les systèmes CASA ont été développés pour aider ces experts à mesurer. Les systèmes commerciaux fermés (cachés) doivent développer leur propre système pour comprendre le système. Comment faire le travail : développer des algorithmes de traitement d’images statiques et dynamiques sur une plate-forme matérielle haute performance. L’idée de base est le même principe, mais profite des progrès technologiques dans le domaine de l’informatique et de l’électronique. Notre objectif principal de ce travail était de mener une enquête sur l’analyse automatique du sperme afin de proposer une méthode pour la conception d’un système de traitement des spermatozoïdes (EL-MED CASA ZRO) utilisant des techniques de traitement d’images mises en œuvre sur un système embarqué. Nous avons proposé l’utilisation du PC embarqué, le Raspberry Pi, comme plateforme matérielle portable et très économique pour le traitement, avec un accès au Cloud pour effectuer un calcul intensif si nécessaire. Pour cette raison, nous prévoyons de mettre cela en œuvre dans un avenir très proche et de publier plus tard, mais pour l’instant, nous classerons cette approche comme une perspective.

هناك ما يقدر بنحو 48.5 مليون من الأزواج الذين يعانون من العقم في العالم حيث أن 20 إلى 30% من الحالات هي من أصل ذكوري، تقدر التكلفة العالمية لعقم الرجال بمبلغ 301.5 مليون دولار. تحليل السائل المنوي بمساعدة نظام (CASA) هو مصطلح يشير إلى تقنيات تحليل السائل المنوي التلقائي أو شبه التلقائي. التحليل الآلي للقذف باستخدام الأجهزة التي تستخدم تقنية التصوير.

تم تطوير أنظمة CASA لمساعدة هؤلاء الخبراء على القياس. يجب على أنظمة الأعمال المغلقة (المخفية) تطوير نظامها الخاص وفهم النظام.

كيفية إنجاز العمل: تطوير خوارزميات معالجة الصور الثابتة والديناميكية على نظام أساسي للأجهزة عالية الأداء. الفكرة الأساسية هي نفس المبدأ، ولكن الاستفادة من التقدم التكنولوجي في مجال المعلوميات والإلكترونيات.

هدفنا الرئيسي من هذا العمل هو دراسة التحليل الآلي للحيوانات المنوية بنجاح من أجل اقتراح طريقة لتصميم نظام معالجة الحيوانات المنوية (EL-MED CASA ZRO) باستخدام تقنيات معالجة الصور، التي تعمل على نظام مدمج.

اقترحنا استخدام الكمبيوتر المدمج، Raspberry كمنصة أجهزة محمولة واقتصادية للغاية للمعالجة مع إمكانية الوصول إلى السحابة لإجراء حسابات مكثفة إذا لزم الأمر. ونحن نخطط لتنفيذ ذلك في المستقبل القريب جدًا وسنصدره لاحقا ولكن في الوقت الحالي هو مشروع لاحق.

Introduction

It is estimated that 48.5 million couples are suffering from infertility worldwide, where 20-30% of cases originate from males, and the market is expected to expand. The global cost of male infertility is estimated at $301.5 million [1]. Computer-aided semen analysis (CASA) is a term that refers to automatic or semi-automatic semen analysis techniques. It involves automated analysis of the ejaculate using equipment employing imaging technology. In 2020, infertility in Algeria affected approximately 15% of couples. The Ministry of Health has quantified this rate to 300,000 infertile couples [2,3,4]. CASA is a method based on image analysis of video sequences. In recent years, semen analysis has become increasingly important in the treatment of fertility problems. Traditionally, sperm quality is assessed by an expert using a microscope to examine the samples. CASA Systems have been developed to help these experts measure the factors that impact sperm quality, such as semen volume, total sperm count, concentration, vitality, motility, or morphology, for the purpose of optimal sperm selection for fertility treatments [5,6].

1. Development Framework and Objectives for Proposed CASA System

1.1. Problematic / proposed solution

1.1.1 Problematic

The commercial systems need to be developed and understood on how to get the job done, i.e., how to develop static and dynamic image processing algorithms on a high-performance hardware platform. Closed (hidden) commercial systems need to develop their own system. Understand the system. How to get the job done: developing static and dynamic image processing algorithms on a high-performance hardware platform? Design: Actually, what are the alternatives and constraints to move forward in the project? The CASA, hardware & software, offers an easy-to-move, small, high-performance, affordable, reliable, and easy-to-use system. Features of an on-board electronic system, with the possibility of finding a compromise between the material and the concept of co-design. Thus, our system is based on Raspberry PI 4 Reinforced by remote processing servers (Hardware resource): Cloud, programming language: PYTHON (open source) free (software), and Matlab easier (programs exist) but with an expensive license (not practical).

1.1.2. Proposed Solution: Proposed CASA

The basic idea operates on the same principle and leverages advancements in computer and electronic technology:

  1. Replacing the human eye with a currently highly sophisticated camera (CMOS).

  2. Image processing (utilizing very advanced tools and programs) employing Artificial Intelligence (Machine Learning) within computer science.

  3. Manual calculations by a high-performance processing unit (currently highly developed in electronics), offering several OPTIONS (GPU, CPU, etc.).

  4. Device selection (Inputs, Outputs): Acquisition and Display (Electronic), such as a Touch Screen, for example.

  5. Connectivity to the internet, employing IOT and CLOUD technologies.

1.2. Objectives

1.2.1. Main objectives

The primary aim is to fabricate a semi-automatic device capable of interpreting slides from various tests prepared by the technician. It proposes a semi-automatic CASA system that can be utilized in:

  • Modern reproductive medicine.

  • Utilizing computer image processing technology.

  • Leveraging advanced artificial intelligence technology. This can be employed in:

  • Automatic sperm identification.

  • Automatic sperm movement tracking.

1.2.2. Secondary Objectives

  • Patent filing.

  • Developing a system capable of rectifying errors in both the technician's readings (biological intelligence) and those made by the automatic CASA (Artificial Intelligence, AI).

2. Materials & Methods

2.1. List of materials (minimum requirement)

  • Raspberry Pi board. • A micro-SD card of 16 GB or more. • A 5 VDC micro-USB power supply.

  • A micro-SD card reader.

  • A keyboard and mouse.

  • An HDMI cable (micro-HDMI for the Pi 4B). • A display with an HDMI input.

2.2. Technology Description

It is a Single-board computer booting from a micro-SD card and running on Linux OS or Windows 10 IoT:

  • Raspberry Pi 4 Model B 4 GB ARM-Cortex-A72 4 x 1.50 GHz.

  • 4 GB RAM, 4 x USB, 2 x Micro HDMI (costing 59 €).

  • Four 64-bit cores supporting dual-screen functionality.

  • Connectivity: Gigabit Ethernet (RJ45), WiFi 802.11b/g/n/ac 5, Bluetooth 5.0.

  • Storage: micro-SD slot available.

  • Dimensions: 10 x 7 x 3 cm, Weight: 50 grams.

Figure 1. The Raspberry PI 4: a PC-on-board (pictured).

Image 1000000000000263000001AF3F76D16A1E94D4BC.png

Image 100000000000023B0000016B981CE35FEC22DA0E.png

Figure 2. Prototype of the proposed system

  Figure 2. Prototype of the proposed system

Conclusion

In our study, we have embarked on the development of an innovative automatic semen analysis system, which harnesses advanced image processing techniques and artificial intelligence (AI), implemented on an accessible, embedded system like Raspberry Pi. This state-of-the-art approach is designed to significantly enhance the accuracy and efficiency of sperm analysis, offering substantial improvements in the realms of reproductive diagnostics and male fertility treatments. By integrating AI into the semen analysis process, we anticipate a substantial improvement in diagnostic accuracy and patient care. This technology is poised to reduce processing times significantly, making these vital analyses more accessible, particularly in regions with limited resources. Furthermore, the system's capability to store and review patient data paves the way for highly personalized fertility tracking.

However, this innovative approach is not without its challenges. Key among these are ensuring robust data protection, accurately interpreting results generated by AI, and seamlessly integrating this technology into existing clinical practices. Successfully addressing these challenges could dramatically enhance the system's utility and reliability. Our vision extends beyond just semen analysis. The potential applications of this AI-based technology are vast and varied, ranging from disease diagnosis and pathology to clinical research, personalized health solutions, and even telemedicine. This expansion could revolutionize diagnostic and treatment processes across a wide array of medical fields. We are also cognizant of our study's limitations, including its external validity and technological dependence. These insights are invaluable, as they guide our future research efforts to further refine and expand the applications of AI in medical diagnostics and treatment. This research not only opens new avenues in reproductive health but also holds the promise of advancing medical science as a whole. As part of our future plans, we aim to implement this system in the near future, with plans to publish our findings. We also intend to merge artificial intelligence with biological insights to minimize errors and optimize semen analysis results. This dual approach will allow us to offer a semi-automatic device to our potential clients, ensuring accurate results and efficient patient file management for better follow-up and management. The completion of our startup is anticipated to open up new budget positions for our clients, facilitating the absorption and recruitment of graduates specializing in reproductive and developmental biology. This integration of cutting-edge technology and specialized human expertise is set to herald a new era in reproductive health diagnostics and treatment.

Agarwal, A., Mulgund, Aditi, Hamada, Alaa, et al. (2015). A unique view on male infertility around the globe. Reproductive Biology and Endocrinology, 13(1), 37.

Rusz A, P.A., Wagenlehner F, Linn T, Diemer T, Scuppe HC, Lohmeyer J, Hossain H, Weidner W. (2012). Influence of urogenital infections and inflammation on semen quality and male fertility. World Journal of Urology, 30, 23-30.

Slama, R., Gou, J. B., & Cordier, S. (2006). Nouvelles avancées dans l’étude de l’influence de l’environnement sur la santé reproductive masculine. Revue d'épidémiologie et de santé publique, 54(2), 167-174.

Stephen. (2002). Environment, lifestyle, and infertility—an intergenerational issue. Nature Medicine, 8(10), S33-S40.

(n.d.). Grandes enquêtes: Enquêtes nationales périnatales. Récupéré de https://colibris.link/6sIfO

(n.d.). [titre de l'article]. Récupéré de https://colibris.link/104w3

Chahinaize Zaoui

Laboratory of Developmental and Differentiation Biology, Ahmed BEN BELLA ORAN1 University et Faculty of Medicine, Ahmed Ben Bella Oran1 University

Diya El-Hak Boucherit

Laboratory of Developmental and Differentiation Biology, Ahmed Ben Bella Oran1 University, Faculty of Medicine, Ahmed Ben Bella Oran1 University et Department of Gynaecology and Obstetrics, EHUO

Keltouma Tadj

Laboratory of Developmental and Differentiation Biology, Ahmed Ben Bella Oran1 University, Faculty of Medicine, Ahmed Ben Bella Oran1 University et Department of Gynaecology and Obstetrics, EHUO

Ibrahim Ouslim

Faculty of Medicine, Ahmed Ben Bella Oran1 University

Moulai Driss Cherif Remal

Faculty of Medicine, Ahmed Ben Bella Oran1 University

Wassila Mohand Arab

Laboratory of Developmental and Differentiation Biology, Ahmed Ben Bella Oran1 University et Department of Gynaecology and Obstetrics, EHUO

Ouslim Mohamed

Mohamed Boudiaf Oran University

Boucherit El Hassen

Laboratory of Developmental and Differentiation Biology, Ahmed Ben Bella Oran1 University, Faculty of Medicine, Ahmed Ben Bella Oran1 University et Department of Gynaecology and Obstetrics, EHUO

Sahraoui Tewfik

Laboratory of Developmental and Differentiation Biology, Ahmed Ben Bella Oran1 University

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